Search results for: Gaussian random weight initialization

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

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Authors: Tomoaki Hashimoto

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Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: optimal control, stochastic systems, random dither, quantization

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Authors: M. Fadlallah, G. Ghibaudo, C. G. Theodorou

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The dynamic variation in memory devices such as the Static Random Access Memory can give errors in read or write operations. In this paper, the effect of low-frequency and random telegraph noise on the dynamic variation of one SRAM cell is detailed. The effect on circuit noise, speed, and length of time of processing is examined, using the Supply Read Retention Voltage and the Read Static Noise Margin. New test run methods are also developed. The obtained results simulation shows the importance of noise caused by dynamic variation, and the impact of Random Telegraph noise on SRAM variability is examined by evaluating the statistical distributions of Random Telegraph noise amplitude in the pull-up, pull-down. The threshold voltage mismatch between neighboring cell transistors due to intrinsic fluctuations typically contributes to larger reductions in static noise margin. Also the contribution of each of the SRAM transistor to total dynamic variation has been identified.

Keywords: low-frequency noise, random telegraph noise, dynamic variation, SRRV

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Authors: Tan Zhang, Zhongjian Wang, Jack Xin, Zhiwen Zhang

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We aim to efficiently compute the spreading speeds of reaction-diffusion-advection (RDA) fronts in divergence-free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) nonlinearity. We study a stochastic interacting particle method (IPM) for the reduced principal eigenvalue (Lyapunov exponent) problem of an associated linear advection-diffusion operator with spatially random coefficients. The Fourier representation of the random advection field and the Feynman-Kac (FK) formula of the principal eigenvalue (Lyapunov exponent) form the foundation of our method implemented as a genetic evolution algorithm. The particles undergo advection-diffusion and mutation/selection through a fitness function originated in the FK semigroup. We analyze the convergence of the algorithm based on operator splitting and present numerical results on representative flows such as 2D cellular flow and 3D Arnold-Beltrami-Childress (ABC) flow under random perturbations. The 2D examples serve as a consistency check with semi-Lagrangian computation. The 3D results demonstrate that IPM, being mesh-free and self-adaptive, is simple to implement and efficient for computing front spreading speeds in the advection-dominated regime for high-dimensional random flows on unbounded domains where no truncation is needed.

Keywords: KPP front speeds, random flows, Feynman-Kac semigroups, interacting particle method, convergence analysis

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Authors: Weisi Guo

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It is well established that there may be running correlations in sequential exam marks due to students sitting in the order of course registration patterns. As such, a random and non-sequential sampling of exam marks is a standard recommended practice. Here, the paper examines a large number of exam data stretching several years across different modules to see the degree to which it is true. Using the real mark distribution as a generative process, it was found that random simulated data had no more sequential randomness than the real data. That is to say, the running correlations that one often observes are statistically identical to chance. Digging deeper, it was found that some high running correlations have students that indeed share a common course history and make similar mistakes. However, at the statistical scale of a module question, the combined effect is statistically similar to the random shuffling of papers. As such, there may not be the need to take random samples for marks, but it still remains good practice to mark papers in a random sequence to reduce the repetitive marking bias and errors.

Keywords: data analysis, empirical study, exams, marking

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Authors: Y. N. Phang, E. F. Loh

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Many researchers have suggested the use of zero inflated Poisson (ZIP) and zero inflated negative binomial (ZINB) models in modeling over-dispersed medical count data with extra variations caused by extra zeros and unobserved heterogeneity. The studies indicate that ZIP and ZINB always provide better fit than using the normal Poisson and negative binomial models in modeling over-dispersed medical count data. In this study, we proposed the use of Zero Inflated Inverse Trinomial (ZIIT), Zero Inflated Poisson Inverse Gaussian (ZIPIG) and zero inflated strict arcsine models in modeling over-dispersed medical count data. These proposed models are not widely used by many researchers especially in the medical field. The results show that these three suggested models can serve as alternative models in modeling over-dispersed medical count data. This is supported by the application of these suggested models to a real life medical data set. Inverse trinomial, Poisson inverse Gaussian, and strict arcsine are discrete distributions with cubic variance function of mean. Therefore, ZIIT, ZIPIG and ZISA are able to accommodate data with excess zeros and very heavy tailed. They are recommended to be used in modeling over-dispersed medical count data when ZIP and ZINB are inadequate.

Keywords: zero inflated, inverse trinomial distribution, Poisson inverse Gaussian distribution, strict arcsine distribution, Pearson’s goodness of fit

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Authors: Flora Babongo, Valerie Chavez

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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

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Authors: Mohammad R. Jalali

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Movement of liquid with a free surface in a container is known as slosh. For instance, slosh occurs when water in a closed tank is set in motion by a free surface displacement, or when liquid natural gas in a container is vibrated by an external driving force, such as an earthquake or movement induced by transport. Slosh is also derived from resonant switching of a natural basin. During sloshing, different types of motion are produced by energy exchange between the liquid and its container. In present study, a numerical model is developed to simulate the nonlinear even harmonic oscillations of free surface sloshing of an initial disturbance to the free surface of a liquid in a closed square basin. The response of the liquid free surface is affected by amplitude and motion frequencies of its container; therefore, sloshing involves complex fluid-structure interactions. In the present study, nonlinear interaction of free surface sloshing of an initial Gaussian hump with its uneven container is predicted numerically. For this purpose, Green-Naghdi (GN) equations are applied as governing equation of fluid field to produce nonlinear second-order and higher-order wave interactions. These equations reduce the dimensions from three to two, yielding equations that can be solved efficiently. The GN approach assumes a particular flow kinematic structure in the vertical direction for shallow and deep-water problems. The fluid velocity profile is finite sum of coefficients depending on space and time multiplied by a weighting function. It should be noted that in GN theory, the flow is rotational. In this study, GN numerical simulations of initial Gaussian hump are compared with Fourier series semi-analytical solutions of the linearized shallow water equations. The comparison reveals that satisfactory agreement exists between the numerical simulation and the analytical solution of the overall free surface sloshing patterns. The resonant free surface motions driven by an initial Gaussian disturbance are obtained by Fast Fourier Transform (FFT) of the free surface elevation time history components. Numerically predicted velocity vectors and magnitude contours for the free surface patterns indicate that interaction of Gaussian hump with its container has localized effect. The result of this sloshing is applicable to the design of stable liquefied oil containers in tankers and offshore platforms.

Keywords: fluid-structure interactions, free surface sloshing, Gaussian hump, Green-Naghdi equations, numerical predictions

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Authors: Ju-Hong Lee, Ching-Wei Liao, Kun-Che Lee

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This paper deals with the problem of using antenna sensors for adaptive beamforming in the presence of random steering mismatch. We present an efficient adaptive array beamformer with robustness to deal with the considered problem. The robustness of the proposed beamformer comes from the efficient designation of the steering vector. Using the received array data vector, we construct an appropriate correlation matrix associated with the received array data vector and a correlation matrix associated with signal sources. Then, the eigenvector associated with the largest eigenvalue of the constructed signal correlation matrix is designated as an appropriate estimate of the steering vector. Finally, the adaptive weight vector required for adaptive beamforming is obtained by using the estimated steering vector and the constructed correlation matrix of the array data vector. Simulation results confirm the effectiveness of the proposed method.

Keywords: adaptive beamforming, antenna array, linearly constrained minimum variance, robustness, steering vector

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Authors: Tian Xia, Yuan Yan Tang

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In order to obtain higher small target detection accuracy, this paper presents an effective algorithm inspired by the local contrast mechanism. The proposed method can enhance target signal and suppress background clutter simultaneously. In the first stage, a enhanced image is obtained using the proposed Weighted Laplacian of Gaussian. In the second stage, an adaptive threshold is adopted to segment the target. Experimental results on two changeling image sequences show that the proposed method can detect the bright and dark targets simultaneously, and is not sensitive to sea-sky line of the infrared image. So it is fit for IR small infrared target detection.

Keywords: small target detection, local contrast, human vision system, Laplacian of Gaussian

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Authors: Levent Basayigit, Sinan Demir, Yusuf Ucar, Burhan Kara

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Many research projects require accurate delineation of the different land cover type of the agricultural area. Especially it is critically important for the definition of specific plants like cannabis. However, the complexity of vegetation stands structure, abundant vegetation species, and the smooth transition between different seconder section stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier. Most of the time, classification distinguishes only between trees/annual or grain. It has been difficult to accurately determine the cannabis mixed with other plants. In this paper, a mixed distribution models approach is applied to classify pure and mix cannabis parcels using Worldview-2 imagery in the Lakes region of Turkey. Five different land use types (i.e. sunflower, maize, bare soil, and cannabis) were identified in the image. A constrained Gaussian mixture discriminant analysis (GMDA) was used to unmix the image. In the study, 255 reflectance ratios derived from spectral signatures of seven bands (Blue-Green-Yellow-Red-Rededge-NIR1-NIR2) were randomly arranged as 80% for training and 20% for test data. Gaussian mixed distribution model approach is proved to be an effective and convenient way to combine very high spatial resolution imagery for distinguishing cannabis vegetation. Based on the overall accuracies of the classification, the Gaussian mixed distribution model was found to be very successful to achieve image classification tasks. This approach is sensitive to capture the illegal cannabis planting areas in the large plain. This approach can also be used for monitoring and determination with spectral reflections in illegal cannabis planting areas.

Keywords: Gaussian mixture discriminant analysis, spectral mixture model, Worldview-2, land parcels

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Authors: Abed Al-Bial, S. Alazazie, A. Shami

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The data were collected from 1992 to 2009 of White Boni sheep maintained at the Regional Research Station in the Central Highlands of Yemen. Data were analyzed to study the growth related traits and their genetic control. The least square means for body weights were 2.26±0.67, 11.14±0.46 and 19.21±1.25 kg for birth weight (BW), weaning weight (WW), six-month weight (WM6), respectively. The pre- and post-weaning average daily weight gains (ADG1 and ADG2) were 106.04±4.98g and 46.21±8.36 g/ day. Significant differences associated with the year of lambing were observed in body weight and weight gain at different stages of growth. Males were heavier and had a higher weight gain than females at almost all stages of growth and differences tended to increase with age. Single-born lambs had a distinct advantage over those born in twin births at all stages of growth. The lambs in the dam’s second to fourth parities were generally of heavier weight and higher daily weight gain than those in other parities. The heritabilities of all body weights, weight gains at different stages of growth were moderate (0.11-0.43). The phenotypic and genetic correlation among the different body weights were positive and high. The genetic correlations of the pre- and post-weaning average daily gains with body weights were hight to moderate, except BW with ADG2.

Keywords: breed, genetics, growth traits, heritability, sheep

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Authors: M. A. Abdel-Wahed, Nayera Elmorsi Hassan, Safaa Shafik Imam, Ola G. El-Farghali, Khadija M. Alian

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Low-birth-weight is a challenging public health problem. Aim: to clarify role of zinc on enhancing catch-up growth of low-birth-weight and find out a proposed relationship between zinc effect on growth and the main growth hormone mediator, IGF-1. Methods: Study is a double-blind-randomized-placebo-controlled trial conducted on low-birth-weight-neonates delivered at Ain Shams University Maternity Hospital. It comprised 200 Low-birth-weight-neonates selected from those admitted to NICU. Neonates were randomly allocated into one of the following two groups: group I: low-birth-weight; AGA or SGA on oral zinc therapy at dose of 10 mg/day; group II: Low-birth-weight; AGA or SGA on placebo. Anthropometric measurements were taken including birth weight, length; head, waist, chest, mid-upper arm circumferences, triceps and sub-scapular skin-fold thicknesses. Results: At 12-month-old follow-up visit, mean weight, length; head (HC), waist, chest, mid-upper arm circumferences and triceps; also, infant’s proportions had values ≥ 10th percentile for weight, length and HC were significantly higher among infants of group I when compared to those of group II. Oral zinc therapy was associated with 24.88%, 25.98% and 19.6% higher proportion of values ≥ 10th percentile regarding weight, length and HC at 12-month-old visit, respectively [NNT = 4, 4 and 5, respectively]. Median IGF-1 levels measured at 6 months were significantly higher in group I compared to group II (median (range): 90 (19 – 130) ng/ml vs. 74 (21 – 130) ng/ml, respectively, p=0.023). Conclusion: Oral zinc therapy in low-birth-weight neonates was associated with significantly more catch-up growth at 12-months-old and significantly higher serum IGF-1 at 6-month-old.

Keywords: low-birth-weight, zinc, catch-up growth, neonates

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Authors: R. K. Saket

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This paper presents design aspects and probabilistic approach for generation reliability evaluation of an alternative resource: municipal waste water based micro hydro power generation system. Annual and daily flow duration curves have been obtained for design, installation, development, scientific analysis and reliability evaluation of the MHPP. The hydro potential of the waste water flowing through sewage system of the BHU campus has been determined to produce annual flow duration and daily flow duration curves by ordering the recorded water flows from maximum to minimum values. Design pressure, the roughness of the pipe’s interior surface, method of joining, weight, ease of installation, accessibility to the sewage system, design life, maintenance, weather conditions, availability of material, related cost and likelihood of structural damage have been considered for design of a particular penstock for reliable operation of the MHPP. A MHPGS based on MWW and SEIG is designed, developed, and practically implemented to provide reliable electric energy to suitable load in the campus of the Banaras Hindu University, Varanasi, (UP), India. Generation reliability evaluation of the developed MHPP using Gaussian distribution approach, safety factor concept, peak load consideration and Simpson 1/3rd rule has presented in this paper.

Keywords: self excited induction generator, annual and daily flow duration curve, sewage system, municipal waste water, reliability evaluation, Gaussian distribution, Simpson 1/3rd rule

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: Muhammad Naeem, Amina Zubari, Abdus Salam, Syed Ali Ayub Bukhari, Naveed Ahmad Khan

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Seventy three wild Labeo bata of different body sizes, ranging from 8.20-16.00 cm total length and 7.4-86.19 g body weight, were studied for the analysis of body composition parameters (Water content, ash content, fat content, protein content) in relation to body size and condition factor. Mean percentage is found as for water 77.71 %, ash 3.42 %, fat 2.20 % and protein content 16.65 % in whole wet body weight. Highly significant positive correlations were observed between condition factor and body weight (r = 0.243). Protein contents, organic content and ash (% wet body weight) increase with increasing percent water contents for Labeo bata while these constituents (% dry body weight) and fat contents (% wet and dry body weight) have no influence on percent water. It was observed that variations in the body constituents have no association to body weight or length.

Keywords: Labeo bata, body size, body composition, condition factor

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Authors: G. L. C. Yap

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Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Gaussian process, long-memory, normalization, value-at-risk, volatility, Whittle estimator

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Authors: M. I. Oshimagye, V. O. Ayuba, P. A. Annune

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The effect of Sublethal Concentrations of Parkia biglobosa pod extract on the growth and survival of Clarias gariepinus juveniles (mean weight 32.73g ± 0.0) were investigated under laboratory conditions for 8 weeks using the static renewal and continuous aeration system. Statistical analysis showed that fish exposed to various concentrations had significantly lower (P<0.05) growth rate than the control groups. The reduction in growth was observed to be directly proportional to increase in concentration. However, at 50 mg/L no significant depression in weight was observed.

Keywords: Clarias gariepinus, Parkia biglobosa, pod, weight

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Authors: Y. Wang, S. Zhang, X. Chen

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The longitudinal compressive strength of fibre reinforced plastic (FRP) possess a large stochastic variability, which limits efficient application of composite structures. This study aims to address how the random fibre packing affects the uncertainty of FRP compressive strength. An novel approach is proposed to generate random fibre packing status by a combination of Latin hypercube sampling and random sequential expansion. 3D nonlinear finite element model is built which incorporates both the matrix plasticity and fibre geometrical instability. The matrix is modeled by isotropic ideal elasto-plastic solid elements, and the fibres are modeled by linear-elastic rebar elements. Composite with a series of different nominal fibre volume fractions are studied. Premature fibre waviness at different magnitude and direction is introduced in the finite element model. Compressive tests on uni-directional CFRP (carbon fibre reinforced plastic) are conducted following the ASTM D6641. By a comparison of 3D FE models and compressive tests, it is clearly shown that the stochastic variation of compressive strength is partly caused by the random fibre packing, and normal or lognormal distribution tends to be a good fit the probabilistic compressive strength. Furthermore, it is also observed that different random fibre packing could trigger two different fibre micro-buckling modes while subjected to longitudinal compression: out-of-plane buckling and twisted buckling. The out-of-plane buckling mode results much larger compressive strength, and this is the major reason why the random fibre packing results a large uncertainty in the FRP compressive strength. This study would contribute to new approaches to the quality control of FRP considering higher compressive strength or lower uncertainty.

Keywords: compressive strength, FRP, micro-buckling, random fibre packing

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Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Isabella Lobo Sasaoka, Felipe Q. da Luz, Zubeyir Salis, Phillipa Hay, Tamiris Gaeta, Paula Costa Teixeira, Táki Cordás, Amanda Sainsbury

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Background: A significant number of people with obesity that seek weight loss treatments experience binge eating episodes. Nonetheless, it is unknown whether binge eating episodes can hinder weight loss outcomes. Objective: To compare weight change in people with or without binge eating submitted to bariatric surgery, pharmacotherapy, nutritional orientation, and/or psychological therapies. Method: We conducted a systematic review with meta-analyses by searching studies in PubMed, American Psychological Association (APA), and Embase. Results: Thirty-four studies were included in our systematic review, and 17 studies were included in the meta-analyses. Overall, we found no significant difference in weight loss between people with or without binge eating submitted to any type of weight loss treatment. Additionally, we found no statistically significant differences in body weight between people with or without binge eating at short and long follow-up assessments following any type of weight loss treatment. We also examined changes in body weight in people with or without binge eating in three additional meta-analyses categorized by the type of weight loss treatment (i.e., behavioural and/or nutritional interventions; bariatric surgery; pharmacotherapy isolated or combined with behavior interventions) and found no difference in weight loss. Eleven out of the 17 studies that were assessed qualitatively (i.e., not included in meta-analyses) did not show differences in weight loss in people with or without binge eating submitted to any type of weight loss treatment. Conclusion: This systematic review with meta-analyses showed no difference in weight loss in people with or without binge eating submitted to a variety of weight loss treatments. Nonetheless, specialized therapies can be required to address eating disorder psychopathology and recurrent binge eating in people with obesity that seek weight loss.

Keywords: obesity, binge eating, weight loss, systematic review, meta-analysis

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Authors: Nayera E. Hassan, Sahar A. El-Masry, Rokia El-Banna, Mohamed S. El Hussieny

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There are several different modalities for treatment of obesity. Common intervention methods for obesity include low-calorie diet, exercise. Also acupuncture has shown good therapeutic results in the treatment of obesity. A recent clinical observation showed that laser acupuncture could reduce body weight and body mass index in obese persons. So, the aim of this research is focused on body composition changes as related to type of intervention, before and after intentional weight loss in overweight and obesity. 76 subjects were included in the study analysis. The present study recommended that every obese female must do lipid profile and fasting blood sugar analysis before weight-loss intervention to take the decision of which method should be used.

Keywords: obesity, weight-loss, body composition, modalities

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Authors: Mehmet Celik, Celal Erbas, Mehtap Baykal, Aygül Kucukgulmez, Mahmut Ali Gokce, Bilge Kaan Tekelioglu

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In this study, determination of differences in fresh meat yield and proximate compositions of different weight groups of sea bream and sea bass grown in cages in Izmir region of the Aegean Sea were aimed. For this purpose, the length and weight of five different weight groups of sea bass (I: 175.8±5.2, II: 227.3±10.2, III: 293.3±21.3, IV: 404±9.9, V: 508.7±46 g) and sea bream (I: 146.6±13.6, II: 239.8±21.7, III: 279.2±20.8, IV: 400.9±10.5, V: 546.8±0.8 g) were measured and the amount of edible and non-edible parts were determined. Besides this, protein, lipid, dry matter, ash, condition factor, HSI and VSI values were compared according to different weight groups for each species. According to the results of analysis, while the absolute meat yields of sea bream was between 69-294 g, it was between 71-252 g for the sea bass and the highest meat yields were found in fifth (V) weight groups of fish for both species. The relative meat yield (%) was determined in weight group II for sea bass and in the IV. group in sea bream with 51.9%. However, the amount of muscle tissue lipids in I. and V. weight groups of sea bream ranged between 3.6 to 11.9 % and ranged between 6.2 to 9.0 % for sea bass respectively. Protein, fillet and ash content increased in direct proportion to the weight. As a result, it can be speculated that when the meat yield and lipid rates were considered, IV. group in sea bream and II. group in sea bass are the most advantageous groups for the consumers. Acknowledgement: This work was supported by the Scientific Research Project Unit of the University of Cukurova, Turkey under grant no FBA-2015-3830.

Keywords: sea bream, sea bass, meat yield, proximate composition, different weight

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Authors: Jeanne Grace, Shereen Currie

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Background: Obesity associated comorbidities increase the risk of morbidity and mortality among employees in the workplace. Objectives: The study aimed to determine the prevalence of obesity and comorbidities like diabetes, hypertension, and hypercholesterolemia associated with obesity within the workplace in South Africa. Methods: A total of 17359 male (n = 8561) and female (n = 8798) employees, aged between 18-64 years (40.8 ± 11.0), from various corporate and industrial companies in South Africa participated in the study. Subjects were assigned to one of five body mass index (BMI) categories, according to their BMI: normal weight, BMI of 18.5‒24.9 kg/m² (n = 7338); overweight, BMI of 25.0‒29.9 kg/m² (n = 6323); obese class I, BMI of 30.0-34.9 kg/m² (n = 2552); obese class II, BMI of 35.0-39.9 kg/m² (n = 782); and obese class III, BMI of ≥ 40 kg/m² (n = 364). Height, weight, blood pressure, random blood glucose, and total cholesterol were measured. Results: The prevalence of normal weight men was 29.2% and women 55.0%; overweight men 46.4% and women 26.7%, obese men 24.4% and women 18.3%. A significant association (p<0.01) of BMI with diabetes, systolic and diastolic hypertension, and hypercholesterolemia were noted. Conclusion: Obesity is strongly associated with adverse comorbidities that may impact employees’ quality of life and performance. If unaddressed, it can increase comorbidities, not only affecting the bottom line of companies but causing morbidity and mortality, including sudden death.

Keywords: body mass index, cholesterol, blood glucose, workplace

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Authors: Siavash Eftekharifar, Tohid Yousefi Rezaii, Mahdi Shamsi

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The purpose of this paper is to exploit compressed sensing (CS) method in order to model and compress the electrocardiogram (ECG) signals at a high compression ratio. In order to obtain a sparse representation of the ECG signals, first a suitable basis matrix with Gaussian kernels, which are shown to nicely fit the ECG signals, is constructed. Then the sparse model is extracted by applying some optimization technique. Finally, the CS theory is utilized to obtain a compressed version of the sparse signal. Reconstruction of the ECG signal from the compressed version is also done to prove the reliability of the algorithm. At this stage, a greedy optimization technique is used to reconstruct the ECG signal and the Mean Square Error (MSE) is calculated to evaluate the precision of the proposed compression method.

Keywords: compressed sensing, ECG compression, Gaussian kernel, sparse representation

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Authors: Michael A. Kraus, Navid Pourmoghaddam, Martin Botz, Jens Schneider, Geralt Siebert

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Fragmentation analysis of tempered glass gives insight into the quality of the tempering process and defines a certain degree of safety as well. Different standard such as the European EN 12150-1 or the American ASTM C 1048/CPSC 16 CFR 1201 define a minimum number of fragments required for soda-lime safety glass on the basis of fragmentation test results for classification. This work presents an approach for the glass breakage pattern prediction using a Voronoi Tesselation over Random Fields. The random Voronoi tessellation is trained with and validated against data from several breakage patterns. The fragments in observation areas of 50 mm x 50 mm were used for training and validation. All glass specimen used in this study were commercially available soda-lime glasses at three different thicknesses levels of 4 mm, 8 mm and 12 mm. The results of this work form a Bayesian framework for the training and prediction of breakage patterns of tempered soda-lime glass using a Voronoi Random Field Tesselation. Uncertainties occurring in this process can be well quantified, and several statistical measures of the pattern can be preservation with this method. Within this work it was found, that different Random Fields as basis for the Voronoi Tesselation lead to differently well fitted statistical properties of the glass breakage patterns. As the methodology is derived and kept general, the framework could be also applied to other random tesselations and crack pattern modelling purposes.

Keywords: glass breakage predicition, Voronoi Random Field Tessellation, fragmentation analysis, Bayesian parameter identification

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Authors: Dmytro O. Plutenko, Alexei D. Kiselev, Mikhail V. Vasnetsov

Abstract:

We present the results of our analytical and computational study of Laguerre-Gaussian (LG) beams scattering by spherical homogeneous isotropic particles located on the axis of the beam. We consider different types of scatterers (dielectric, metallic and double negative metamaterials) and different polarizations of the LG beams. A possibility to generate photonic nanojets using metallic and double negative metamaterial Mie scatterers is shown. We have studied the properties of such nonclassical nanojets and discovered new types of the nanojets characterized by zero on-axes magnetic (or electric) field with the electric (or magnetic) field polarized along the z-axis.

Keywords: double negative metamaterial, Laguerre-Gaussian beam, Mie scattering, optical vortices, photonic nanojets

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Authors: Mohamed O. Babana

Abstract:

In wireless channel multipath is the propagation phenomena where the transmitted signal arrive at the receiver side with many of paths, the signal at these paths arrive with different time delay the results is random signal fading due to intersymbols interference(ISI). This paper deals with identification of orthogonal frequency division multiplexing (OFDM) technology, and how it is used to overcome intersymbol interference due to multipath. Also investigates the effect of Additive White Gaussian Noise Channel (AWGN) on OFDM using multi-level modulation of Phase Shift Keying (PSK), computer simulation to calculate the bit error rate (BER) under AWGN channel is applied. A comparison study is carried out to obtain the Bit Error Rate performance for OFDM to identify the best multi-level modulation of PSK.

Keywords: intersymbol interference(ISI), bit error rate(BER), modulation, multiplexing, simulation

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Authors: Muhammad Naeem, Abdus Salam, Sumera Yasmin, Abir Ishtiaq

Abstract:

In the present study, eighty-three wild Oreochromis aureus of different body size ranging 5.3-14.6 cm in total length were collected from the River Chenab, District Muzzafer Garh, Pakistan to investigate the parameters of length –weight, length-length relationships and condition factor in relation to size. Each fish was measured and weighed on arrival at laboratory. Log transformed regressions were used to test the allometric growth. Length-weight relationship was found highly significant (r = 0.964; P < 0.01). The values of exponent “ b” in Length–weight regression (W=aL^b), deviated from 3, showing isometric growth (b = 2.75). Results for LLRs indicated that these are highly correlated (P < 0.001). Condition factor (K) found constant with increasing body weight, however, showed negative influence with increasing total length.

Keywords: lenght-weight, Oreochromis aureus, morphometric study

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Authors: A. A. Ahmadi, A. R. Pishevar, M. Nili

Abstract:

As the test gas in a gun tunnel is non-isentropically compressed and heated by a light weight piston. Here, first consideration is the optimum piston weight. Although various aspects of the influence of piston weight on gun tunnel performance have been studied, it is not possible to decide from the existing literature what piston weight is required for optimum performance in various conditions. The technique whereby the piston is rapidly brought to rest at the end of the gun tunnel barrel, and the resulted peak pressure is equal in magnitude to the final equilibrium pressure, is called the equilibrium piston technique. The equilibrium piston technique was developed to estimate the equilibrium piston mass; but this technique cannot give an appropriate estimate for the optimum piston weight. In the present work, a gun tunnel with diameter of 3 in. is described and its performance is investigated numerically to obtain the effect of piston and its weight. Numerical results in the present work are in very good agreement with experimental results. Significant influence of the existence of a piston is shown by comparing the gun tunnel results with results of a conventional shock tunnel in the same dimension and same initial condition. In gun tunnel, an increase of around 250% in running time is gained relative to shock tunnel. Also, Numerical results show that equilibrium piston technique is not a good way to estimate suitable piston weight and there will be a lighter piston which can increase running time of the gun tunnel around 60%.

Keywords: gun tunnel, hypersonic flow, piston, shock tunnel

Procedia PDF Downloads 348