Preparation and keeping quality of hot smoked mackerel

A method has been standardised for the production of smoke cured mackerel by dry salting in the ratio of 1:8 salt to fish followed by smoking in a traditional smoke chamber at 70±5°C for 5h. The smoke was generated by burning moist coconut husk and saw dust. The product obtained by this method had shelf-lives of 105, 95 and 6 days in chilled storage (0 to 2°C) refrigerated storage (10±2°C) and at room temperature (29±2°C) respectively.

Improvement in quality and shelf-life of whole dried prawns

A simple and effective method is suggested to improve the quality and shelf-life of commercial whole dried thelly prawns (Metapenaeus dobsoni). Treatment of whole prawns in 10% brine containing 0.1% citric acid for 20 min followed by drying in sun yield a product having good physical, chemical and organoleptic characteristics. Retardation of fungal incidence, reduction in total volatile nitrogen (TVBN) and improvement in flavour are some of the advantages of the treatment. The treated product has a shelf-life around 30 weeks compared to 20 weeks for untreated control and 7 weeks for commercial sample.

Selection and application of a suitable sampling method for quantitative and qualitative evaluation of lab-lab

Milkfish and prawn pond operation in the Philippines is often associated with lab-lab culture. Lab-lab is a biological complex of blue-green algae, diatoms, bacteria and various animals which form a mat at the bottom of nursery ponds or floating patches along the margins of ponds. This complex is considered the most favorable food of milkfish in brackishwater ponds. Variations in the quantity and quality of lab-lab between and within areas of a 1,000 sq. m. pond was determined over 2 culture periods (6 month duration) and the applicability and suitability of stratified random sampling as a method of sampling lab-lab was evaluated.

Adoption of recommended quality control practices by fish processing factories

Responses to mailed questionnaires from 31 fish processing factories revealed that for 55 recommended practices in quality control, the percentage of adopters varied from 21.43 to 100.The adoption index was not correlated to any of five variables studied. The mean adoption index did not differ significantly between five other criteria related to fish processing. Rate of rejection or reprocessing at the factory itself was highly correlated with the amount of water used per tonne of processed material.

The survey on growth and survival rate parameters with slurry and comparison by common method

This project was on “Study of Slurry, as an enrichment compound, on growth and survival parameters of Rutilus firisii kutum Kamensky 1901 larva and compare with routine condition according to hypothesis that use of Slurry, fertile organic compound, to increase the efficiency of survivorship and growth of Rutilus firisii and in other hand adaptation of natural food was performance.” The object of this project is to compare growth of Rutilus firisii and in usual condition and the condition of use Slurry The experiences performed in culture and propagation center Dr. Yousefpour decent (Associan of Dr. Beheshti culture and propagation) in Siahkal village, 32 Km far from southeast, in North of Iran. In this plan, three different treatments and related these nine pools , in 1.7 hec area (in same condition) were determined so that the density of storage was 1.7 million/hec larva. In this research at first treatment m we use slurry as enrichment compound during larval within a period of 13 days, and it used all the days of during larval in second treatment. Then the result of this study compared to control treatment. The results have shown the level of this study compared to control treatment. The results have shown the level of survivorship in pools were nutrition by slurry was 1.7 million times or twice than pools were nutrition with usual concentrate. In addition, growth coefficient such as daily weight growing (DWG) index, daily length growth (DLG), specific growth ratio (SGR) were measured in this case. All of these parameters in slurry treatment were shown noticeable enhancement in first treatment Thereof in the first week there was significant difference (P<0.001) between the average of length and weight in first week , and in the second week there was a significant difference (P<0.05) between them.

Effect of organophosphate, diazinon on some immunophysiological, haematological and histological variable of Rutilus frisii kutum (Kamensky,1901)

The acute toxicity and effects of diazinon on some haematological parameters of kutum (Rutilus frisii kutum, Kamensky, 1901) weighing 613.33 g±157.06 g were studied under static water quality conditions at 15°C ± 2ºC in winter and spring 2009. The effective physical and chemical parameters of water were pH= 7-8.2, dh= 300mg/L (caco3), DO= 7 ppm and T= 15°C±2ºC. The first test was primarily to determine the effects of acute toxicity (LC5096 h) of the agricultural toxicant diazinon (emulsion 60%) on kutum male brood stocks. For this purpose, 4 treatments were used to test toxicity; each treatment was repeated in 3 tanks with 9 fish per treatment and with 180 litres water capacity. After obtaining the final results, the information was analysed statistically with Probit version 1.5 (USEPA, 1985), and we determined the LC10, LC50 and LC90 values at 24 hours, 48 hours, 72 hours and 96 hours; the maximum allowable concentration value (LC5096 h divided by 10) (TRC, 1984); and the degree of toxicity. The second stage of testing consists of four treatments: LC0= 0 as experimental treatment, treatment A with a concentration of LC1= 0.107 mg/L, treatment B with concentration of LC5= 0.157 mg/L, treatment C with concentration of MAC value= 0.04 mg/L. Male brood stocks of kutum were treated with these concentrations for 45 days. Experiments were carried out under static conditions based on the standard TRC, 1984 method over 45 days. Our results show that long-term exposure to diazinon causes a decrease in the erythrocyte count (RBC), haemoglobin (Hb), haematocrit (PCV), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC), leucocyte count (WBC), lymphocyte, testosterone, iron (Fe), sodium (Na), lactate dehydrogenase (LDH), and cholinesterase (CHeS). In addition, diazinon also causes an increase in prolymphocyte, aspartate aminotransferase (AST), cholesterol, alkaline phosphatase (ALP) and adrenaline (P<0.05). There are no significant effects on monocyte, eosinophil, magnesium (Mg), chloride (Cl), glucose (BS), urea (BUN), uric acid (U.A), triglyceride (TG), calcium (Ca), albumin (Alb), total protein (TP), cortisol, noradrenaline and high density lipoprotein (HDL) levels in kutum male brood stocks (P>0.05). Pathology results showed toxin diazinon no effect on average weight and fish body length, the average weight of heart, brain, spleen, liver, kidney and liver index but caueses decrease of gonad weigth and gonad index and also, cause complications of tissue necrosis, vascular congestion, inflammation in the liver, a sharp reduction in the number of glomeruli, necrosis, vascular congestion and haemorage in the kidney, capsule thickening and fibrosis, atrophy, vascular congestion, macrophages release increased, increasing sediment Hemosiderine and thickening of artery walls in the spleen, atrophy, fibrosis and necrosis in testis , vascular congestion, increased distance between the myocardium and fibrous string in heart and neuronal loss, vascular congestion and edema in the brain of kutum male brood stocks.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Improving model quality through computer controlled saturation

In dynamic centrifuge modelling, fluids with enhanced viscosity are often used to correct for the discrepancy in time scaling. However, great care must be taken when using a high viscosity fluid that hydraulic gradients during saturation do not become high enough to cause excessive model disturbance. This paper introduces the CAM-Sat system which aims to improve the saturation process by continually controlling the fluid flow into the model, limiting it to rates low enough to avoid model disturbance. A new method for measuring the fluid flow rate is then described, and its implementation & improvement to the system is discussed. © 2010 Taylor & Francis Group, London.

Machine vision based concrete surface quality assessment

Manually inspecting concrete surface defects (e.g., cracks and air pockets) is not always reliable. Also, it is labor-intensive. In order to overcome these limitations, automated inspection using image processing techniques was proposed. However, the current work can only detect defects in an image without the ability of evaluating them. This paper presents a novel approach for automatically assessing the impact of two common surface defects (i.e., air pockets and discoloration). These two defects are first located using the developed detection methods. Their attributes, such as the number of air pockets and the area of discoloration regions, are then retrieved to calculate defects’ visual impact ratios (VIRs). The appropriate threshold values for these VIRs are selected through a manual rating survey. This way, for a given concrete surface image, its quality in terms of air pockets and discoloration can be automatically measured by judging whether their VIRs are below the threshold values or not. The method presented in this paper was implemented in C++ and a database of concrete surface images was tested to validate its performance. Read More: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29CO.1943-7862.0000126?journalCode=jcemd4

A classification of data quality assessment methods

Data quality (DQ) assessment can be significantly enhanced with the use of the right DQ assessment methods, which provide automated solutions to assess DQ. The range of DQ assessment methods is very broad: from data profiling and semantic profiling to data matching and data validation. This paper gives an overview of current methods for DQ assessment and classifies the DQ assessment methods into an existing taxonomy of DQ problems. Specific examples of the placement of each DQ method in the taxonomy are provided and illustrate why the method is relevant to the particular taxonomy position. The gaps in the taxonomy, where no current DQ methods exist, show where new methods are required and can guide future research and DQ tool development.

Spray drying: An alternative synthesis method for polycationic oxide compounds

Synthesis of polycationic compounds by the spray-drying technique is an interesting alternative in the domain of aqueous precursor synthesis methods. Spray drying yields high quality samples with good reproducibility. The possibility of scaling up for production of large quantities with fast processing time is well established by the commercial availability of powders of various compositions. In this paper, we have discussed the advantages and limitations of this method and demonstrated its interest by synthesizing a few polycationic compounds selected for their attractive properties of thermoelectricity [Bi1.68Ca2Co1.69O 8, La0.95A0.05CoO3 (A=Ca, Sr, Ba)] or magnetoresistance [La0.70A0.30MnO3 (A=Sr, Ba)]. We have confirmed the quality of these samples by reporting their structure, magnetic and transport properties. © 2010 Elsevier Ltd All rights reserved.

Generalized power method for sparse principal component analysis

In this paper we develop a new approach to sparse principal component analysis (sparse PCA). We propose two single-unit and two block optimization formulations of the sparse PCA problem, aimed at extracting a single sparse dominant principal component of a data matrix, or more components at once, respectively. While the initial formulations involve nonconvex functions, and are therefore computationally intractable, we rewrite them into the form of an optimization program involving maximization of a convex function on a compact set. The dimension of the search space is decreased enormously if the data matrix has many more columns (variables) than rows. We then propose and analyze a simple gradient method suited for the task. It appears that our algorithm has best convergence properties in the case when either the objective function or the feasible set are strongly convex, which is the case with our single-unit formulations and can be enforced in the block case. Finally, we demonstrate numerically on a set of random and gene expression test problems that our approach outperforms existing algorithms both in quality of the obtained solution and in computational speed. © 2010 Michel Journée, Yurii Nesterov, Peter Richtárik and Rodolphe Sepulchre.

Introducing carbon diffusion barriers for uniform, high-quality graphene growth from solid sources.

Carbon diffusion barriers are introduced as a general and simple method to prevent premature carbon dissolution and thereby to significantly improve graphene formation from the catalytic transformation of solid carbon sources. A thin Al2O3 barrier inserted into an amorphous-C/Ni bilayer stack is demonstrated to enable growth of uniform monolayer graphene at 600 °C with domain sizes exceeding 50 μm, and an average Raman D/G ratio of <0.07. A detailed growth rationale is established via in situ measurements, relevant to solid-state growth of a wide range of layered materials, as well as layer-by-layer control in these systems.

Warping trajectories for video synchronization

Temporal synchronization of multiple video recordings of the same dynamic event is a critical task in many computer vision applications e.g. novel view synthesis and 3D reconstruction. Typically this information is implied, since recordings are made using the same timebase, or time-stamp information is embedded in the video streams. Recordings using consumer grade equipment do not contain this information; hence, there is a need to temporally synchronize signals using the visual information itself. Previous work in this area has either assumed good quality data with relatively simple dynamic content or the availability of precise camera geometry. In this paper, we propose a technique which exploits feature trajectories across views in a novel way, and specifically targets the kind of complex content found in consumer generated sports recordings, without assuming precise knowledge of fundamental matrices or homographies. Our method automatically selects the moving feature points in the two unsynchronized videos whose 2D trajectories can be best related, thereby helping to infer the synchronization index. We evaluate performance using a number of real recordings and show that synchronization can be achieved to within 1 sec, which is better than previous approaches. Copyright 2013 ACM.