Archives-December 

An almost complex manifold is a smooth manifold accoutred with smooth linear complex structure on each tangent space. Almost complex structures have important applications on symplectic geometry. M is a symplectic manifold such that it accoutred with a closed nondegenerate di¤erential 2-form then it called the symplectic form. Symplectic mani- folds arise naturally in abstract formulations of classical mechanics and analytical mechanics as the cotangent bundles of manifolds. In classical mechanics, dynamic movements with Euler-Lagrange and Hamilton equa- tions is found. We, using two complex structures, examined mechanical systems on symplectic geometry.

Ceramic whiteware represents one of the most complex ceramics, formulated from a mix of china clay, ball clay and quartz are sintered to conform a ceramic composite. Ceramic whiteware has excellent technical characteristics. Nowadays, research of new materials, for example non-hazardous wastes, that are able to replace the traditional fluxing agent without changing the process or quality of the final products has been realized. The aim of this work is to study the possibility of the use of quartz, in ceramic whiteware mixtures, for manufacturing of electrical ceramic whiteware bodies. It was prepared by mixtures containing different amounts of china clay, ball clay, feldspar and quartz. The samples were fired reaching different maximum temperatures in the range 950-1250 ºC, with a soaking time of 1 hour. The fired samples were characterized and the use of small amounts of quartz in addition with whiteware samples showed good results of mechanical technological properties. The optimum quartz percentage (25%) S1 samples at 1250 ?C gives the maximum bending strength.

Data dependencies between instructions have traditionally limited the ability of processors to execute instructions in parallel. Data value predictors are used to overcome these dependencies by guessing the outcomes of instructions in a program. Because mispredictions can result in a significant performance decrease, most data value predictors include a confidence estimator that indicates whether a prediction should be used or not.Much research has been done recently in the area of data value prediction as a means of overcoming these data dependencies [7,8,9,10,11,17,18,20,21]. The goal of data value prediction is to guess the outcome of an instruction before the instruction is actually executed, allowing future instructions that depend on its outcome to be executed sooner. Data value predictors are usually designed to look for patterns among the data produced in repeated iterations of static instructions. Accurate prediction can be attained when the repeated outcomes of a particular instruction follow easily discernable patterns.This paper presents a global approach to confidence estimation in which the prediction accuracy of previous instructions is used to estimate the confidence of the current prediction. Data value prediction is done using perceptrons and Support Vector Machines are used to identify which past instructions affect the accuracy of a prediction and to decide based on their results whether the prediction is likely to be correct or not .

Myositis ossificans circumscribed (MOC) is a rare, benign condition characterized by heterotopic ossification of the striated muscles often occurring in young subjects. We propose to illustrate from an observation, the aspects realized by the ossification myositis circumscribed in conventional radiology, in tomodensitometry in order to avoid the potential diagnostic confusion with a malignant bone tumor.

In this research we use the logistic function to demonstrate the existence of a stationary point as a type of a non-wandering set in topological dynamical systems or dynamical systems without any loss of generality.

Oxidation and microbial degradation are the limiting factors in the quality and acceptability of meat product. Deleterious effect from synthetic additives usage has increase the demand for natural additive sources to ensure safety of meat products and consumers. Meatfloss was prepared from semitendinosus muscle following a standard procedure. Mentha pepperita powder (MPP) inclusion in shredding recipe was 0, 1.25% and 2.50%. The study was completely randomized and replicated threes. Protein, ash, saturated and unsaturated fatty acids of freshly prepared meatfloss, Thiobarbituric Acid Reactive Substances (TBARS) (mgMA/kg) and Total Heterophilic counts (THC) (cfu/gx103) at 0, 1, 2, 3, 4 weeks were assessed using standard procedures. Protein (40.90%; 40.87%) and ash (6.06%; 7.27%) of 1.25% and 2.50% MPP meatfloss were higher (P<0.05) than 39.19% (protein) and 4.07% (ash) meatfloss with no MPP. No significant differences (P>0.05) among saturated and unsaturated fatty acids. Irrespective of the storage period, TBARS levels (1.14-1.40); (1.13-1.20) and THC (0.30-0.23); (0.33-0.03) of 1.25% and 2.50% MPP meatfloss were higher (P<0.05) than 1.14-2.00 (TBARS) and 0.41-2.40 (THC) of meatfloss with no MPP. Reduced levels of thiobarbituric acid reactive substances and low total heterophilic counts highlighted the potential usage of Mentha pepperita as efficient inhibitors of oxidative and microbial processes. 

Flow Shop Scheduling is the combinational optimization & NP-hard (i.e. Non-deterministic Polynomial-time hard) problems. In Permutation Flow Shops, the sequence of the jobs is same on all machines. In a Flow Shop Scheduling problem with ‘n’ jobs that should be processed on ‘m’ machines. The job can be processed on at most one machine; meanwhile one machine can be processed at most one job. A significant research effort has been committed for sequencing jobs in flow shop to minimizing the make span. Optimization algorithms such as Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO) & Neighborhood Search have played a significant role in solving small scale flow shop scheduling problems. In this paper a recently developed Teaching Learning Based Optimization (TLBO) is proposed method to solve the flow shop scheduling problems to minimize the make span. The proposed algorithm is tested on Taillard Benchmark problems and results are compared with Palmer’s & CDS Heuristic methods. The results show that the proposed algorithm is efficient in producing optimal solution and simple, easy to understand.

To evaluate the effectiveness and clinical significance of pattern visual evoked potential (P-VEP) as a predictor of occlusion therapy for patients with strabismic and amblyopia(squint eye).Methods: A total of 34 consecutive children with anisometropic squint were included in this study. All patients underwent a full initial ophthalmologic and orthoptic evaluation. P-VEP test was performed in all cases and binocular vision was tested and recorded Part-time occlusion therapy was performed by using adhesive patches. Results: The mean (±SEM) cycloplegic refractive error was +5.6 ± 0.6 diopters (D) in the squint eyes and +1.8 ± 0.2 D in the normal eye. The mean levels of best-corrected visual acuity were statistically differed between each measurement for occlusion therapy (for each, p < 0.05). The ratio of the patients with binocular vision increased after 6 months occlusion therapy and the difference was statistically significant (p<0.05). In addition, P100 amplitude improved at each visit and the difference was significant when compared with baseline values (for each, p < 0.05). Conclusions: P100 amplitude of the P-VEP test parallels the improvement in subjective visual acuity in squint eyes under occlusion therapy. Therefore, this test may be useful in monitoring the visual acuity in the preverbal or non-verbal patched patients.

In this Research, a new method has been proposed in order to classify the mental tasks which represent the Electroencephalogram (EEG) signal as time series. Time series are kind of data format which depict signal voltage varieties in time domain. Different parts of the different signals have different powers, so in first step and in the preprocessing, signal partitioning into several fixed windows is needed. Toward the extracting appropriate features from each EEG signal window, PCA algorithm is used. So for each window, a feature vector is made by PCA, and a general vector is created from these primary vectors. In order to refuse redundancy caused by non-important windows, the best combination of such vectors, that have the best results in classification, should be probed. Toward this goal, two feature extraction methods, Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), are applied. K-Nearest Neighbor (KNN) was used as fitness function for PSO and GA. These methods select such windows whose combination of feature vectors are best and increase TP (true positive) of the classifier. The results show that GA and PSO improve the power of classification, but GA is more efficient.

Many applications use TCP as the transport layer for reliable data transfer for wireless connections to integrate seamlessly into the Internet. Some of the assumptions made during the design of traditional TCP may not be suitable for an infrastructure-less network environment, because TCP invokes the congestion control mechanism even if the packet loss is due to the link failure. On the other hand TCP-F that is able to distinguish link failure from congestion through feedback from the intermediate nodes and takes appropriate action. This paper compares the performance of TCP-F with traditional TCP through simulation.