A measurement-based prioritization scheme for handovers in mobilecellular networks

A method of improving the quality of service in mobile cellular systems based on prioritization of handover requests is presented. The objective is to improve perceived quality of cellular service by minimizing both the probability of forced termination of ongoing calls due to handover failures and the degradation in spectrum utilization. A model based on a multiple-priority nonpreemptive queuing discipline is developed. New calls are blocked if all channels are occupied. Handover requests are queued such that as soon as a channel is available, it is offered to the mobile subscriber with the measurement results closest to the minimum acceptable power level for communication. Service rate is given by channel occupancy time distribution and is assumed to be exponential. The performance of a cellular system employing the proposed handover policy is evaluated analytically and by simulation, and results are compared to those obtained when the cellular system employs nonprioritized call handling and first-in/first-out queuing discipline. This provides lower probability of forced termination and less call blocking, less reduction in traffic, and less delay     

Effect of the infestation by Prostephanus truncatus Horn, Sitophilus zeamais Mots, or Sitotroga cerealella Oliver, on the concentration of amino acids in corn proteins

The amino acid concentration in the protein of batches of corn kernel subjected to infestation by P. truncatus, S. zeamais or S. cerealella was measured. For each insect species three development stages were studied, larvae, at the emergence of the first generation, and longer. Differences between the control and each of the nine infested batches were observed for most of the amino acids. The only pattern of differences consistent in magnitude, significance and sign, was a fall in leucine and isoleucine and a raise in tryptophan concentration. The chemical scores of all samples were similar to the control, except in the case of infestation by larvae of S. cerealella in which it decreased 15%.     

Review of methods for predicting in situ volume change movement of expansive soil over time

The soil movement information over time is required for the design of foundations placed in expansive soils. This information is also helpful for the assessment of pre-wetting and controlled wetting mitigation alternatives for expansive soils. Several researchers during the past fifteen years have proposed different methods for the prediction of the soil movements over time. The available methods can be categorized into(i) consolidation theory-based methods,(ii) water content-based methods, and(iii) suction-based methods. In this paper, a state-of-the-art of the prediction methods is succinctly summarized. The methods are critically reviewed in terms of their predictive capacity along with their strengths and limitations. The review highlights the need for prediction methods that are conceptually simple yet efficient for use in conventional engineering practice for different types of expansive soils.     

Cost optimization of mixed feeds with the particle swarm optimization method

In this study, the best mixed feed was prepared by using the algorithm of particle swarm optimization (PSO) and by taking into account the breeding type and method of the poultries and various farm animals (cattle, sheep, rabbit), their needs, ages, and feeding costs and optimizing them all. Results obtained through PSO were compared through linear programming and real-coded genetic algorithm. According to the results that were obtained, PSO produces more rapid, more stable, and optimum values.     

Applied Genetic Programming for Predicting Specific Cutting Energy for Cutting Natural Stones

In the processing of marbles and other natural stones, the major cost involved in sawing with circular diamond sawblades is the energy cost. This paper reports a new and efficient approach to the formulation of SE_cut using gene expression programming (GEP) based on not only rock characteristics but also design and operating parameters. Twenty-three rock types classified into four groups were cut using three types of circular diamond saws at different feed rates, depths of cut, and peripheral speeds. The input parameters used to develop the GEP-based SE_cut prediction model were as follows: physico-mechanical rock characteristics (uniaxial compressive strength, Shore scleroscope hardness, Schmidt rebound hardness, and Bohme surface abrasion), operating parameters (feed rate, depth of cut, and peripheral speed), and a design variable (diamond concentration in the sawblade). The performance of the model was comprehensively evaluated on the basis of statistical criteria such as R² (0.95).     

ANN-based prediction of surface and hole quality in drilling of AISI D2 cold work tool steel

This paper focuses on artificial neural network (ANN)-based modeling of surface and hole quality in drilling of AISI D2 cold work tool steel with uncoated titanium nitride (TiN) and titanium aluminum nitride (TiAlN) monolayer- and TiAlN/TiN multilayer-coated-cemented carbide drills. A number of drilling experiments were conducted at all combinations of different cutting speeds (50, 55, 60, and 65 m/min) and feed rates (0.063 and 0.08 mm/rev) to obtain training and testing data. The experimental results showed that the surface roughness (Ra) and roundness error (Re) values were obtained with the TiN monolayer- and TiAlN/TiN multilayer-coated drills, respectively. Using some of the experimental data in training stage, an ANN model was developed. To evaluate the performance of the developed ANN model, ANN predictions were compared with the experimental results. It was found that the determination coefficient values are more than 0.99 for both training and test data. Root mean square error and mean error percentage values were very low. ANN results showed that ANN can be used as an effective modeling technique in accurate prediction of the Ra and Re.     

Optimization of cutting parameters on drill bit temperature in drilling by Taguchi method

In this study, the optimization of the cutting parameters on drill bit temperature in drilling was performed. Al 7075 work piece and the uncoated and Firex® coated carbide drills in the experimental were used. The optimization of the cutting parameters was evaluated by Taguchi method. The control factors were considered as the cutting speed, feed rate and cutting tool. Taguchi method was used to determining the settings of cutting parameters. The L₁₈ orthogonal array was used in experimental planning. The most significant control factors affected on drill bit temperature measurements was obtained by using analysis of variance (ANOVA). Taguchi design method exhibit a good performance in the optimization of cutting parameters on drill bit temperature measurements. In addition, the empirical equations of drill bit temperatures were derived by using regression analysis. The obtained equations results compared with the drill bit temperature measurement results. The empirical equations results indicated a good agreement with experimental results.     

Instrumentation and Computer Interface of an Automated Experimental Cryopreservation Apparatus

ABSTRACT

A process suitable for cooling and warming the isolated rat heart by a perfusion technique was designed, built, automated and tested in the areas of normothermia, hypothermia, cryopro-tectant (CPA) administration and cooling to -22°C. The major benefits were in the application of computer control technology to a complex field like cryopreservation with promising results.     

Nanomechanical characterization by double-pass force-distance mapping

We demonstrate high speed force-distance mapping using a double-pass scheme. The topography is measured in tapping mode in the first pass and this information is used in the second pass to move the tip over the sample. In the second pass, the cantilever dither signal is turned off and the sample is vibrated. Rapid (few kHz frequency) force-distance curves can be recorded with small peak interaction force, and can be processed into an image. Such a double-pass measurement eliminates the need for feedback during force-distance measurements. The method is demonstrated on self-assembled peptidic nanofibers.     

Formation of MoTe2 Nanotubes by Electron Irradiation

Abstract

In this article, we report the study and to our knowledge the first production of MoTe₂ (Molybdenum telluride) nanotubes by irradiation with high doses of electrons. a 2 MeV Van de Graaff accelerator was used to irradiate the samples at the following conditions: 1.3 MeV voltage, 5μA current, dose rate 25 kGy/min, total dosage 1000 kGy. the samples were examined in a high-resolution transmission electron microscope. the principal characteristic observed was huge nanotubes of the order of several nm long and few nm wide, which seems to be hollow. It is necessary to point out that searching carefully through out other areas of the sample, we were not able to locate either onionlike structures or nanoparticles as it is usual to find in graphite, WS₂ or MoS₂.