Multi-indicator Active Queue Management Method

A considerable number of applications are running over IP networks. This increased the contention on the network resource, which ultimately results in congestion. Active queue management (AQM) aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance. AQM methods implement different techniques in accordance with congestion indicators, such as queue length and average queue length. The performance of the network is evaluated using delay, loss, and throughput. The gap between congestion indicators and network performance measurements leads to the decline in network performance. In this study, delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM. The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability, which is responsible for managing the router buffer. The experimental results, based on two sets of experiments, have shown that the proposed method outperformed the existing benchmark algorithms including RED, ERED and BLUE algorithms. For instance, in the first experiment, the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms. In addition, the proposed method outperformed the benchmark algorithms in terms of packet loss, packet dropping, and packet retransmission. Overall, the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.     

State estimation and experimental verification of a robotic vehicle with six in-wheel drives using Kalman filter

Microsystem Technologies - In this research we present an algorithm for a six-wheeled robotic vehicle with articulated suspension (RVAS) to estimate the vehicle velocity and acceleration states,...     

Modeling and control of a finger-like mechanism using bending shape memory alloys

Microsystem Technologies - In this research a biologically inspired finger-like mechanism similar to human musculoskeletal system is developed based on Shape Memory Alloys (SMAs). SMA actuators are...     

On an evolutionary approach for constrained optimization problem solving

Over the last few decades, many different evolutionary algorithms have been introduced for solving constrained optimization problems. However, due to the variability of problem characteristics, no single algorithm performs consistently over a range of problems. In this paper, instead of introducing another such algorithm, we propose an evolutionary framework that utilizes existing knowledge to make logical changes for better performance. The algorithmic aspects considered here are: the way of using search operators, dealing with feasibility, setting parameters, and refining solutions. The combined impact of such modifications is significant as has been shown by solving two sets of test problems: (i) a set of 24 test problems that were used for the CEC2006 constrained optimization competition and (ii) a second set of 36 test instances introduced for the CEC2010 constrained optimization competition. The results demonstrate that the proposed algorithm shows better performance in comparison to the state-of-the-art algorithms.     

CR-39 as a gamma dosimeter: Dielectric and infrared studies

The relative permittivity, , and dielectric loss factor, tan , were measured in the frequency range 50–10⁵ Hz for the solid state track detector CR-39 irradiated with -rays (5–100 kGy). The variation of and tan with -dose have been interpreted in terms of structural changes as emphasized from infrared spectra. A mathematical model has been introduced describing the use of CR-39 as a dielectric dosimeter.     

Additive Behavior in Copper Electrorefining

This paper reports on the mode of action of two different organic additives—gelatine and thiourea—during the electrorefining of copper from acid copper sulfate solutions. Gelatine increases the cathode current efficiency and produces smoother deposits up to a certain level of concentration, beyond which, however, these effects are diminished by the steric hinderance of bulky molecular entities adsorbed to the electrode surface. Thiourea decreases the cathode current efficiency when present at concentrations around 5 mg/1. Nonetheless, it improves deposit quality. In higher concentrations, thiourea increases the cathodic current efficiency but also promotes nodule formation and rough deposits. The degradation and/or hydrolysis of both additives and the various interactions with the electrode surface and with cupric ions in solution are also examined.     

Physicochemical investigation of the decomposition products of ammonium metal carboxylates: ammonium ferric citrate hydrate

The thermal decomposition up to 400 °C of ammonium ferric citrate hydrate, of unknown structure and formula weight, was studied by thermogravimetry, differential thermal analysis, infrared (IR) spectroscopy and X-ray diffractometry. The possible identities of the formula weight and the intermediate products of calcination are discussed. The results revealed that the parent material is amorphous and contains two moles of water and two moles of ammonia. Decomposition takes place via six weight-loss processes, three endothermic (90–230 °C) and three exothermic (240–298 °C), leading eventually to the formation of Fe₂O₃. The intermediate solid products are mainly unstable amorphous oxycarbonates, as indicated by X-ray and IR spectroscopies. The gas-phase decomposition products identified by IR spectroscopy are NH₃, CO₂, CO, CH₃COCH₃, CH₄ and NH₄OH. Surface area measurement and scanning electron microscopy showed that Fe₂O₃, the final product at 400 °C, hada surface area of 40 m²/g and good crystalline and porous character.     

Feature extraction and ML techniques for static gesture recognition

The main objective of this study is to explore the utility of a neural network-based approach in hand gesture recognition. The proposed system presents two recognition algorithms to recognize a set of six specific static hand gestures, namely open, close, cut, paste, maximize, and minimize. The hand gesture image is passed through three stages: preprocessing, feature extraction, and classification. In the first method, the hand contour is used as a feature that treats scaling and translation of problems (in some cases). However, the complex moment algorithm is used to describe the hand gesture and to treat the rotation problem in addition to scaling and translation. The back-propagation learning algorithm is employed in the multilayer neural network classifier. The second method proposed in this article achieves better recognition rate than the first method.     

Methanol oxidation on Au/TiO2 catalysts

We have investigated the adsorption and reaction of methanol with Au/TiO₂ catalysts using a pulsed flow reactor, DRIFTS and TPD. The TiO₂ (P25) surface adsorbed a full monolayer of methanol, much of it in a dissociative manner, forming methoxy groups associated with the cationic sites, and hydroxyl groups at the anions. The methoxy is relatively stable until 250 °C, at which point decomposition occurs, producing mainly dimethyl ether by a bimolecular surface reaction. As the concentration of methoxy on the surface diminishes, so the mechanism reverts to a de-oxygenation pathway, producing mainly methane and water (at ~330 °C in TPD), but also with some coincident CO and hydrogen. Au catalysts were prepared by the deposition-precipitation method to give Au loadings between 0.5–3 wt %. The effect of low levels of Au on the reactivity is marked. The pathway which gives methane, which is characteristic of titania, remains, but a new feature of the reaction is the evolution of CO₂ and H₂ at lower temperature (a peak is seen in TPD at 220 °C), and the elimination of the DME-producing state. Clearly this is associated with the presence of Au and appears to be due to the production of a formate species on the surface of the Au component. This formate species is mainly involved in the reaction of methanol with the Au/TiO₂ catalysts which results in a combustion pathway being followed, with complete conversion occurring by ~130 °C.