Vision Based UAV Attitude Estimation: Progress and Insights

Unmanned aerial vehicles (UAVs) are increasingly replacing manned systems in situations that are dangerous, remote, or difficult for manned aircraft to access. Its control tasks are empowered by computer vision technology. Visual sensors are robustly used for stabilization as primary or at least secondary sensors. Hence, UAV stabilization by attitude estimation from visual sensors is a very active research area. Vision based techniques are proving their effectiveness and robustness in handling this problem. In this work a comprehensive review of UAV vision based attitude estimation approaches is covered, starting from horizon based methods and passing by vanishing points, optical flow, and stereoscopic based techniques. A novel segmentation approach for UAV attitude estimation based on polarization is proposed. Our future insightes for attitude estimation from uncalibrated catadioptric sensors are also discussed.     

A method for real power transfer allocation using multivariable regression analysis

A multivariable regression (MVR) approach is proposed to identify the real power transfer between generators and loads. Based on solved load flow results, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then, the results of MNE method and load flow information are utilized to determine suitable regression coefficients using MVR model to estimate the power transfer. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of the MVR output compared to that of the MNE method. The error of the estimate of MVR method ranges from 0.001 4 to 0.007 9. Furthermore, when compared to MNE method, MVR method computes generator contribution to loads within 26.40 ms whereas the MNE method takes 360 ms for the calculation of same real power transfer allocation. Therefore, MVR method is more suitable for real time power transfer allocation.     

Sensitivity compensating nonlinear control: Exact model based approach

A novel sensitivity compensating nonlinear control (SCNC) approach is proposed within generic model control (GMC) framework for processes exhibiting input sensitivity. The proposed approach consists of defining a new process, control law and set point such that the determined control action drives the original process to its desired set point. External reset feedback (ERF), used to compensate for input saturation, is extended to higher relative degree systems as extended ERF (EERF), and is incorporated in the context of SCNC approach. The proposed control algorithms are evaluated by application to an open-loop unstable CSTR control problem and a multi-product semi-batch polymerization reactor temperature control problem. The present study illustrates the versatility of the proposed SCGMC schemes compared to the basic GMC schemes in terms of output tracking and smoother input profiles. SCNC can be extended to other nonlinear model based controllers where the control law can be expressed analytically.     

Optimum operating conditions for an adsorption cryocooler: a case of activated carbon + nitrogen system

Adsorption cryocoolers are among the possible options for obtaining cryogenic temperatures, in particular for small cooling capacity applications such as cooling of infra red detectors. They need to be optimized for liquid yield. The performance of thermal compressors therein pivots around the adsorption characteristics of the adsorbent + adsorbate combination and how effectively one could pack requisite amounts of adsorbent into a given volume of the compressor housing. In addition, the overall performance of the cooler is a function of limits of operating temperatures and pressures across the compressor. This paper proposes a performance indicator—the product of liquid yield and the uptake efficiency of the compressor—and evaluates its values for various possible operating conditions for one specimen of activated carbon. It is shown that there is a limited domain of operation and that there is a condition of best performance within that domain.     

Implementing two methods in GIS software for indoor routing: an empirical study

Multimedia Tools and Applications - With increasing demands for indoor GIS, indoor routing and analysis attracts attention from both GIS and architecture worlds. This paper aimes to provide...     

Ionization coefficient of monolayer graphene nanoribbon

A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy E_t and the distance travelled by electron gaining E_t. In addition, ionization threshold energy is semi-analytically modelled for GNR. During modelling, we justify our assumptions using analytical modelling and comparison with simulation. Furthermore, it is shown that conventional silicon models are not valid for calculation of ionization coefficient of GNR. Finally, the profile of ionization is presented using the proposed models and the results are compared with that of silicon.     

Polymer Membrane Electrodes for Sensitive Potentiometric Determination of β-blockers

ABSTRACT

The construction of PVC matrix-type β-blockers (sotalol, carvedilol, and betaxolol) ion selective electrodes and their use for direct potentiometry of their respective species are described. The proposed sensors are based on the complex ion associates of β-blockers with tungstophosphate (TP) and Ammonium Reineckate (Rein) ionophoris in poly vinyl chloride membrane (PVC) with Dioctylphthalate (DOP) plasticizer. The four electrodes (Beta-TP), (Sota-TP), (Carve-TP), and (Cave-Rein) show stable potential response with near Nernstian slope of 50.8, 33.7, 32.35, and 33 mv per decade, range of concentration 10?2–10?7 M β-blockers. Selectivity coefficients data obtained for 11 different organic and inorganic ions are presented. The electrodes have fast response time (30 and 40 s) and were used over wide range of pH 4.5–8.5. Validation of the method according to the quality assurance standers shows suitability of proposed sensors for use in the quality control assessment of these drugs. The results obtained for the determination of β-blockers with the proposed electrodes show average recoveries of 100.78% and a mean standard deviation of ±1.2. The nominal are obtained. The data agree well with those obtained by standard methods.     

Anticonvulsant Profiles of Certain New 6-Aryl-9-substituted-6,9-diazaspiro-[4.5]decane-8,10-diones and 1-Aryl-4-substituted-1,4-diazaspiro[5.5]undecane-3,5-diones

Synthesis and anticonvulsant potential of certain new 6-aryl-9-substituted-6,9-diazaspiro[4.5]decane-8,10-diones (6a–l) and 1-aryl-4-substituted-1,4-diazaspiro[5.5]undecane-3,5-diones (6m–x) are reported. The intermediates 1-[(aryl)(cyanomethyl)amino]cycloalkanecarboxamides (3a–f) were prepared via adopting Strecker synthesis on the proper cycloalkanone followed by partial hydrolysis of the obtained nitrile functionality and subsequent N-cyanomethylation. Compounds 3a–f were subjected to complete nitrile hydrolysis to give the respective carboxylic acid derivatives 4a–f which were cyclized under mild conditions to give the spiro compounds 5a–f. Ultimately, compounds 5a–f were alkylated or aralkylated to give the target compounds 6a–i and 6m–u. On the other hand, compounds 6j–l and 6v–x were synthesized from the intermediates 5a–f through alkylation, dehydration and finally tetrazole ring formation. Anticonvulsant screening of the target compounds 6a–x revealed that compound 6g showed an ED₅₀ of 0.0043 mmol/kg in the scPTZ screen, being about 14 and 214 fold more potent than the reference drugs, Phenobarbital (ED₅₀ = 0.06 mmol/kg) and Ethosuximide (ED₅₀ = 0.92 mmol/kg), respectively. Compound 6e exhibited an ED₅₀ of 0.019 mmol/kg, being about 1.8 fold more potent than that of the reference drug, Diphenylhydantoin (ED₅₀ = 0.034 mmol/kg) in the MES screen. Interestingly, all the test compounds 6a–x did not show any minimal motor impairment at the maximum administered dose in the neurotoxicity screen.