Production Throughput Modeling under Five Uncertain Variables Using Bayesian Inference

Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Repatriates in the Kazakhstan: The Problems of Migration and Adaptation to the Historic Homeland

The article is devoted to Kazakh repatriates and their migration to Kazakhstan as historical homeland, and also addresses the problem of migrants- adaptation in the republic, particularly in Almaty oblast (region). The authors used up-to-date statictics and materials of the Department of Migration Committee to analyze the newcomers- number and features of the repatriate-s location in this oblast. Having studied this region they were able to identify the main reasons why Kazakh Diaspora in Central Asia, Iran, Avganistana and Turkey is eager to come back to their historic homeland along with repatriates adaptation to the republic.

Ethanol Fuelled HCCI Engine: A Review

The greenhouse effect and limitations on carbon dioxide emissions concern engine maker and the future of the internal combustion engines should go toward substantially and improved thermal efficiency engine. Homogeneous charge compression ignition (HCCI) is an alternative high-efficiency technology for combustion engines to reduce exhaust emissions and fuel consumption. However, there are still tough challenges in the successful operation of HCCI engines, such as controlling the combustion phasing, extending the operating range, and high unburned hydrocarbon and CO emissions. HCCI and the exploitation of ethanol as an alternative fuel is one way to explore new frontiers of internal combustion engines with an eye towards maintaining its sustainability. This study was done to extend database knowledge about HCCI with ethanol a fuel.

Mathematical Modeling of SISO based Timoshenko Structures – A Case Study

This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.

Endothelial-Cell-Mediated Displacement of Extracellular Matrix during Angiogenesis

Mechanical interaction between endothelial cells (ECs) and the extracellular matrix (or collagen gel) is known to influence the sprouting response of endothelial cells during angiogenesis. This influence is believed to impact on the capability of endothelial cells to sense soluble chemical cues. Quantitative analysis of endothelial-cell-mediated displacement of the collagen gel provides a means to explore this mechanical interaction. Existing analysis in this context is generally limited to 2D settings. In this paper, we investigate the mechanical interaction between endothelial cells and the extracellular matrix in terms of the endothelial-cellmediated displacement of the collagen gel in both 2D and 3D. Digital image correlation and Digital volume correlation are applied on confocal reflectance image stacks to analyze cell-mediated displacement of the gel. The skeleton of the sprout is extracted from phase contrast images and superimposed on the displacement field to further investigate the link between the development of the sprout and the displacement of the gel.

Cr, Fe and Se Contents of the Turkish Black and Green Teas and the Effect of Lemon Addition

Tea is consumed by a big part of the world-s population. It has an enormous importance for the Turkish culture. Nearly it is brewed every morning and evening at the all houses. Also it is consumed with lemon wedge. Habitual drinking of tea infusions may significantly contribute to daily dietary requirements of elements. Different instrumental techniques are used for determination of these elements. But atomic and mass spectroscopic methods are preferred most. In these study chromium, iron and selenium contents after the hot water brewing of black and green tea were determined by Optical Emission Spectroscopy (ICP-OES). Furthermore, effect of lemon addition on chromium, iron and selenium concentration tea infusions is investigated. Results of the investigation showed that concentration of chromium, iron and selenium increased in black tea with lemon addition. On the other hand only selenium is increased with lemon addition in green tea. And iron concentration is not detected in green tea but its concentration is determined as 1.420 ppm after lemon addition.

The Study of the Interaction between Catanionic Surface Micelle SDS-CTAB and Insulin at Air/Water Interface

Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.

Modified Fuzzy ARTMAP and Supervised Fuzzy ART: Comparative Study with Multispectral Classification

In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.

Energy Absorption and Axial Tearing Behaviour of Metallic Tubes Using Angled Dies: Experimental and Numerical Simulation

This paper concerns about the experimental and numerical investigations of energy absorption and axial tearing behaviour of aluminium 6060 circular thin walled tubes under static axial compression. The tubes are received in T66 heat treatment condition with fixed outer diameter of 42mm, thickness of 1.5mm and length of 120mm. The primary variables are the conical die angles (15°, 20° and 25°). Numerical simulations are carried on ANSYS/LS-DYNA software tool, for investigating the effect of friction between the tube and the die.

Mechanical Characteristics of Spaghetti Enriched with Whole Soy Flour

The influence of full-fat soy flour (FFSF) and extrusion conditions on the mechanical characteristics of dry spaghetti were evaluated. Process was performed with screw speed of 10-40rpm and water circulating temperature of 35-70°C. Data analysis using mixture design showed that this enrichment resulted in significant differences in mechanical strength.

OPTIMAL Placement of FACTS Devices by Genetic Algorithm for the Increased Load Ability of a Power System

This paper presents Genetic Algorithm (GA) based approach for the allocation of FACTS (Flexible AC Transmission System) devices for the improvement of Power transfer capacity in an interconnected Power System. The GA based approach is applied on IEEE 30 BUS System. The system is reactively loaded starting from base to 200% of base load. FACTS devices are installed in the different locations of the power system and system performance is noticed with and without FACTS devices. First, the locations, where the FACTS devices to be placed is determined by calculating active and reactive power flows in the lines. Genetic Algorithm is then applied to find the amount of magnitudes of the FACTS devices. This approach of GA based placement of FACTS devices is tremendous beneficial both in terms of performance and economy is clearly observed from the result obtained.

Modeling and Optimization of Aggregate Production Planning - A Genetic Algorithm Approach

The Aggregate Production Plan (APP) is a schedule of the organization-s overall operations over a planning horizon to satisfy demand while minimizing costs. It is the baseline for any further planning and formulating the master production scheduling, resources, capacity and raw material planning. This paper presents a methodology to model the Aggregate Production Planning problem, which is combinatorial in nature, when optimized with Genetic Algorithms. This is done considering a multitude of constraints of contradictory nature and the optimization criterion – overall cost, made up of costs with production, work force, inventory, and subcontracting. A case study of substantial size, used to develop the model, is presented, along with the genetic operators.

Mirror Neuron System Study on Elderly Using Dynamic Causal Modeling fMRI Analysis

Dynamic Causal Modeling (DCM) functional Magnetic Resonance Imaging (fMRI) is a promising technique to study the connectivity among brain regions and effects of stimuli through modeling neuronal interactions from time-series neuroimaging. The aim of this study is to study characteristics of a mirror neuron system (MNS) in elderly group (age: 60-70 years old). Twenty volunteers were MRI scanned with visual stimuli to study a functional brain network. DCM was employed to determine the mechanism of mirror neuron effects. The results revealed major activated areas including precentral gyrus, inferior parietal lobule, inferior occipital gyrus, and supplementary motor area. When visual stimuli were presented, the feed-forward connectivity from visual area to conjunction area was increased and forwarded to motor area. Moreover, the connectivity from the conjunction areas to premotor area was also increased. Such findings can be useful for future diagnostic process for elderly with diseases such as Parkinson-s and Alzheimer-s.

Approximate Method of Calculation of Inviscid Hypersonic Flow

In the present work steady inviscid hypersonic flows are calculated by approximate Method. Maslens' inverse method is the chosen approximate method. For the inverse problem, parabolic shock shape is chosen for the two-dimensional flow, and the body shape and flow field are calculated using Maslen's method. For the axisymmetric inverse problem paraboloidal shock is chosen and the surface distribution of pressure is obtained.

Connectivity Characteristic of Transcription Factor

Transcription factors are a group of proteins that helps for interpreting the genetic information in DNA. Protein-protein interactions play a major role in the execution of key biological functions of a cell. These interactions are represented in the form of a graph with nodes and edges. Studies have showed that some nodes have high degree of connectivity and such nodes, known as hub nodes, are the inevitable parts of the network. In the present paper a method is proposed to identify hub transcription factor proteins using sequence information. On a complete data set of transcription factor proteins available from the APID database, the proposed method showed an accuracy of 77%, sensitivity of 79% and specificity of 76%.

Evolution of Quality Function Deployment (QFD) via Fuzzy Concepts and Neural Networks

Quality Function Deployment (QFD) is an expounded, multi-step planning method for delivering commodity, services, and processes to customers, both external and internal to an organization. It is a way to convert between the diverse customer languages expressing demands (Voice of the Customer), and the organization-s languages expressing results that sate those demands. The policy is to establish one or more matrices that inter-relate producer and consumer reciprocal expectations. Due to its visual presence is called the “House of Quality" (HOQ). In this paper, we assumed HOQ in multi attribute decision making (MADM) pattern and through a proposed MADM method, rank technical specifications. Thereafter compute satisfaction degree of customer requirements and for it, we apply vagueness and uncertainty conditions in decision making by fuzzy set theory. This approach would propound supervised neural network (perceptron) for MADM problem solving.

Analysis of FWM Penalties in DWDM Systems Based on G.652, G.653, and G.655 Optical Fibers

This paper presents an investigation of the power penalties imposed by four-wave mixing (FWM) on G.652 (Single- Mode Fiber - SMF), G.653 (Dispersion-Shifted Fiber - DSF), and G.655 (Non-Zero Dispersion-Shifted Fiber - NZDSF) compliant fibers, considering the DWDM grids suggested by the ITU-T Recommendations G.692, and G.694.1, with uniform channel spacing of 100, 50, 25, and 12.5 GHz. The mathematical/numerical model assumes undepleted pumping, and shows very clearly the deleterious effect of FWM on the performance of DWDM systems, measured by the signal-to-noise ratio (SNR). The results make it evident that non-uniform channel spacing is practically mandatory for WDM systems based on DSF fibers.

Direct Numerical Simulation of Oxygen Transfer at the Air-Water Interface in a Convective Flow Environment and Comparison to Experiments

Two-dimensional Direct Numerical Simulation (DNS) of high Schmidt number mass transfer in a convective flow environment (Rayleigh-B'enard) is carried out and results are compared to experimental data. A fourth-order accurate WENO-scheme has been used for scalar transport in order to aim for a high accuracy in areas of high concentration gradients. It was found that the typical spatial distance between downward plumes of cold high concentration water and the eddy size are in good agreement with experiments using a combined PIV-LIF technique for simultaneous and spatially synoptic measurements of 2D velocity and concentration fields.

Laplace Decomposition Approximation Solution for a System of Multi-Pantograph Equations

In this work we adopt a combination of Laplace transform and the decomposition method to find numerical solutions of a system of multi-pantograph equations. The procedure leads to a rapid convergence of the series to the exact solution after computing a few terms. The effectiveness of the method is demonstrated in some examples by obtaining the exact solution and in others by computing the absolute error which decreases as the number of terms of the series increases.

Impact of Music on Brain Function during Mental Task using Electroencephalography

Music has a great effect on human body and mind; it can have a positive effect on hormone system. Objective of this study is to analysis the effect of music (carnatic, hard rock and jazz) on brain activity during mental work load using electroencephalography (EEG). Eight healthy subjects without special musical education participated in the study. EEG signals were acquired at frontal (Fz), parietal (Pz) and central (Cz) lobes of brain while listening to music at three experimental condition (rest, music without mental task and music with mental task). Spectral powers features were extracted at alpha, theta and beta brain rhythms. While listening to jazz music, the alpha and theta powers were significantly (p < 0.05) high for rest as compared to music with and without mental task in Cz. While listening to Carnatic music, the beta power was significantly (p < 0.05) high for with mental task as compared to rest and music without mental task at Cz and Fz location. This finding corroborates that attention based activities are enhanced while listening to jazz and carnatic as compare to Hard rock during mental task.