A Study of the Garbage Enzyme's Effects in Domestic Wastewater

“Garbage enzyme", a fermentation product of kitchen waste, water and brown sugar, is claimed in the media as a multipurpose solution for household and agricultural uses. This study assesses the effects of dilutions (5% to 75%) of garbage enzyme in reducing pollutants in domestic wastewater. The pH of the garbage enzyme was found to be 3.5, BOD concentration about 150 mg/L. Test results showed that the garbage enzyme raised the wastewater-s BOD in proportion to its dilution due to its high organic content. For mixtures with more than 10% garbage enzyme, its pH remained acidic after the 5-day digestion period. However, it seems that ammonia nitrogen and phosphorus could be removed by the addition of the garbage enzyme. The most economic solution for removal of ammonia nitrogen and phosphorus was found to be 9%. Further tests are required to understand the removal mechanisms of the ammonia nitrogen and phosphorus.

Product-Based Industrial Information Systems (Application to the Steel Industry)

This paper shows a simple and effective approach to the design and implementation of Industrial Information Systems (IIS) oriented to control the characteristics of each individual product manufactured in a production line and also their manufacturing conditions. The particular products considered in this work are large steel strips that are coiled just after their manufacturing. However, the approach is directly applicable to coiled strips in other industries, like paper, textile, aluminum, etc. These IIS provide very detailed information of each manufactured product, which complement the general information managed by the ERP system of the production line. In spite of the high importance of this type of IIS to guarantee and improve the quality of the products manufactured in many industries, there are very few works about them in the technical literature. For this reason, this paper represents an important contribution to the development of this type of IIS, providing guidelines for their design, implementation and exploitation.

Synthesis and Characterization of PEG-Silane Functionalized Iron Oxide Nanoparticle as MRI T2 Contrast Agent

Iron oxide nanoparticle was synthesized by reactive-precipitation method followed by high speed centrifuge and phase transfer in order to stabilized nanoparticles in the solvent. Particle size of SPIO was 8.2 nm by SEM, and the hydraulic radius was 17.5 nm by dynamic light scattering method. Coercivity and saturated magnetism were determined by VSM (vibrating sample magnetometer), coercivity of nanoparticle was lower than 10 Hc, and the saturated magnetism was higher than 65 emu/g. Stabilized SPIO was then transferred to aqueous phase by reacted with excess amount of poly (ethylene glycol) (PEG) silane. After filtration and dialysis, the SPIO T2 contrast agent was ready to use. The hydraulic radius of final product was about 70~100 nm, the relaxation rates R2 (1/T2) measured by magnetic resonance imaging (MRI) was larger than 200(sec-1).

Contaminated Soil Remediation with Hydrogen Peroxide Oxidation

The hydrogen peroxide treatment was able to remediate chlorophenols, polycyclic aromatic hydrocarbons, diesel and transformer oil contaminated soil. Chemical treatment of contaminants adsorbed in peat resulted in lower contaminants- removal and required higher addition of chemicals than the treatment of contaminants in sand. The hydrogen peroxide treatment was found to be feasible for soil remediation at natural soil pH. Contaminants in soil could degrade with the addition of hydrogen peroxide only indicating the ability of transition metals ions and minerals of these metals presented in soil to catalyse the reaction of hydrogen peroxide decomposition.

On Methodologies for Analysing Sickness Absence Data: An Insight into a New Method

Sickness absence represents a major economic and social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model selection and a critical analysis of the temporal trends, the occurrence and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model applicability to complicated longitudinal data.

Biodiesel Production from High Iodine Number Candlenut Oil

Transesterification of candlenut (aleurites moluccana) oil with methanol using potassium hydroxide as catalyst was studied. The objective of the present investigation was to produce the methyl ester for use as biodiesel. The operation variables employed were methanol to oil molar ratio (3:1 – 9:1), catalyst concentration (0.50 – 1.5 %) and temperature (303 – 343K). Oil volume of 150 mL, reaction time of 75 min were fixed as common parameters in all the experiments. The concentration of methyl ester was evaluated by mass balance of free glycerol formed which was analyzed by using periodic acid. The optimal triglyceride conversion was attained by using methanol to oil ratio of 6:1, potassium hydroxide as catalyst was of 1%, at room temperature. Methyl ester formed was characterized by its density, viscosity, cloud and pour points. The biodiesel properties had properties similar to those of diesel oil, except for the viscosity that was higher.

Effects of Xylanase and Cellulase Production during Composting of EFB and POME using Fungi

Empty Fruit Bunches (EFB) and Palm Oil Mill Effluent (POME) are two main wastes from oil palm industries which contain rich lignocellulose. Degradation of EFB and POME by microorganisms will produce hydrolytic enzyme which will degrade cellulose and hemicellulose during composting process. However, normal composting takes about four to six months to reach maturity. Hence, application of fungi into compost can shorten the period of composting. This study identifies the effect of xylanase and cellulase produced by Aspergillus niger and Trichoderma virens on composting process using EFB and POME. The degradation of EFB and POME indicates the lignocellulolytic capacity of Aspergillus niger and Trichoderma virens with more than 7% decrease in hemicellulose and more than 25% decrease in cellulose for both inoculated compost. Inoculation of Aspergillus niger and Trichoderma virens also increased the enzyme activities during the composting period compared to the control compost by 21% for both xylanase and cellulase. Rapid rise in the activities of cellulase and xylanase was observed by Aspergillus niger with the highest activities of 14.41 FPU/mg and 3.89 IU/mg, respectively. Increased activities of cellulase and xylanase also occurred in inoculation of Trichoderma virens with the highest activities obtained at 13.21 FPU/mg and 4.43 IU/mg, respectively. Therefore, it is evident that the inoculation of fungi can increase the enzyme activities hence effectively degrading the EFB and POME.

Ionic Liquid Pretreatment and Enzymatic Hydrolysis of Wood Biomass

Pretreatment of lignocellulosic biomass materials from poplar, acacia, oak, and fir with different ionic liquids (ILs) containing 1-alkyl-3-methyl-imidazolium cations and various anions has been carried out. The dissolved cellulose from biomass was precipitated by adding anti-solvents into the solution and vigorous stirring. Commercial cellulases Celluclast 1.5L and Accelerase 1000 have been used for hydrolysis of untreated and pretreated lignocellulosic biomass. Among the tested ILs, [Emim]COOCH3 showed the best efficiency, resulting in highest amount of liberated reducing sugars. Pretreatment of lignocellulosic biomass using glycerol-ionic liquids combined pretreatment and dilute acid-ionic liquids combined pretreatment were evaluated and compared with glycerol pretreatment, ionic liquids pretreatment and dilute acid pretreatment.

A Comparison of Marginal and Joint Generalized Quasi-likelihood Estimating Equations Based On the Com-Poisson GLM: Application to Car Breakdowns Data

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Position Awareness Mechanisms for Wireless Sensor Networks

A Wireless sensor network (WSN) consists of a set of battery-powered nodes, which collaborate to perform sensing tasks in a given environment. Each node in WSN should be capable to act for long periods of time with scrimpy or no external management. One requirement for this independent is: in the presence of adverse positions, the sensor nodes must be capable to configure themselves. Hence, the nodes for determine the existence of unusual events in their surroundings should make use of position awareness mechanisms. This work approaches the problem by considering the possible unusual events as diseases, thus making it possible to diagnose them through their symptoms, namely, their side effects. Considering these awareness mechanisms as a foundation for highlevel monitoring services, this paper also shows how these mechanisms are included in the primal plan of an intrusion detection system.

Rigorous Modeling of Fixed-Bed Reactors Containing Finite Hollow Cylindrical Catalyst with Michaelis-Menten Type of Kinetics

A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.

Chaotic Response and Bifurcation Analysis of Gear-Bearing System with and without Porous Effect under Nonlinear Suspension

This study presents a systematic analysis of the dynamic behaviors of a gear-bearing system with porous squeeze film damper (PSFD) under nonlinear suspension, nonlinear oil-film force and nonlinear gear meshing force effect. It can be found that the system exhibits very rich forms of sub-harmonic and even the chaotic vibrations. The bifurcation diagrams also reveal that greater values of permeability may not only improve non-periodic motions effectively, but also suppress dynamic amplitudes of the system. Therefore, porous effect plays an important role to improve dynamic stability of gear-bearing systems or other mechanical systems. The results presented in this study provide some useful insights into the design and development of a gear-bearing system for rotating machinery that operates in highly rotational speed and highly nonlinear regimes.

Development of a Simple laser-based 2D Compensating System for the Contouring Accuracy of Machine Tools

The dynamical contouring error is a critical element for the accuracy of machine tools. The contouring error is defined as the difference between the processing actual path and commanded path, which is implemented by following the command curves from feeding driving system in machine tools. The contouring error is resulted from various factors, such as the external loads, friction, inertia moment, feed rate, speed control, servo control, and etc. Thus, the study proposes a 2D compensating system for the contouring accuracy of machine tools. Optical method is adopted by using stable frequency laser diode and the high precision position sensor detector (PSD) to performno-contact measurement. Results show the related accuracy of position sensor detector (PSD) of 2D contouring accuracy compensating system was ±1.5 μm for a calculated range of ±3 mm, and improvement accuracy is over 80% at high-speed feed rate.

Multiple Moving Talker Tracking by Integration of Two Successive Algorithms

In this paper, an estimation accuracy of multiple moving talker tracking using a microphone array is improved. The tracking can be achieved by the adaptive method in which two algorithms are integrated, namely, the PAST (Projection Approximation Subspace Tracking) algorithm and the IPLS (Interior Point Least Square) algorithm. When either talker begins to speak again after a silent period, an appropriate feasible region for an evaluation function of the IPLS algorithm might not be set. Then, the tracking fails due to the incorrect updating. Therefore, if an increment of the number of active talkers is detected, the feasible region must be reset. Then, a low cost realization is required for the high speed tracking and a high accuracy realization is desired for the precise tracking. In this paper, the directions roughly estimated using the delayed-sum-array method are used for the resetting. Several results of experiments performed in an actual room environment show the effectiveness of the proposed method.

Software Reliability Prediction Model Analysis

Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Reconstitute Information about Discontinued Water Quality Variables in the Nile Delta Monitoring Network Using Two Record Extension Techniques

The world economic crises and budget constraints have caused authorities, especially those in developing countries, to rationalize water quality monitoring activities. Rationalization consists of reducing the number of monitoring sites, the number of samples, and/or the number of water quality variables measured. The reduction in water quality variables is usually based on correlation. If two variables exhibit high correlation, it is an indication that some of the information produced may be redundant. Consequently, one variable can be discontinued, and the other continues to be measured. Later, the ordinary least squares (OLS) regression technique is employed to reconstitute information about discontinued variable by using the continuously measured one as an explanatory variable. In this paper, two record extension techniques are employed to reconstitute information about discontinued water quality variables, the OLS and the Line of Organic Correlation (LOC). An empirical experiment is conducted using water quality records from the Nile Delta water quality monitoring network in Egypt. The record extension techniques are compared for their ability to predict different statistical parameters of the discontinued variables. Results show that the OLS is better at estimating individual water quality records. However, results indicate an underestimation of the variance in the extended records. The LOC technique is superior in preserving characteristics of the entire distribution and avoids underestimation of the variance. It is concluded from this study that the OLS can be used for the substitution of missing values, while LOC is preferable for inferring statements about the probability distribution.

Analysis of Microalgae Lipids Isolated from Basin of Kazakhstan, to Assess the Prospects of Practical Use

It was analyzed of fatty acid composition of 16 strains of microalgae lipid fractions isolated from different basins of Kazakhstan and characterized by stable active growth in the laboratory. Three species of green microalgae (Oocystis rhomboideus, Chlorococcum infusionum, Dictyochlorella globosa) and three species of diatoms (Synedra sp., Nitzshia sp., Pleurosigma attenuatum) are characterized by a high content of lipids and are promising for further study as a source of polyunsaturated fatty acids.

Treatment of Recycled Concrete Aggregates by Si-Based Polymers

The recycling of concrete, bricks and masonry rubble as concrete aggregates is an important way to contribute to a sustainable material flow. However, there are still various uncertainties limiting the widespread use of Recycled Concrete Aggregates (RCA). The fluctuations in the composition of grade recycled aggregates and their influence on the properties of fresh and hardened concrete are of particular concern regarding the use of RCA. Most of problems occurring while using recycled concrete aggregates as aggregates are due to higher porosity and hence higher water absorption, lower mechanical strengths, residual impurities on the surface of the RCA forming weaker bond between cement paste and aggregate. So, the reuse of RCA is still limited. Efficient polymer based treatment is proposed in order to reuse RCA easier. The silicon-based polymer treatments of RCA were carried out and were compared. This kind of treatment can improve the properties of RCA such as the rate of water absorption on treated RCA is significantly reduced.

A Study on the Differential Diagnostic Model for Newborn Hearing Loss Screening

According to the statistics, the prevalence of congenital hearing loss in Taiwan is approximately six thousandths; furthermore, one thousandths of infants have severe hearing impairment. Hearing ability during infancy has significant impact in the development of children-s oral expressions, language maturity, cognitive performance, education ability and social behaviors in the future. Although most children born with hearing impairment have sensorineural hearing loss, almost every child more or less still retains some residual hearing. If provided with a hearing aid or cochlear implant (a bionic ear) timely in addition to hearing speech training, even severely hearing-impaired children can still learn to talk. On the other hand, those who failed to be diagnosed and thus unable to begin hearing and speech rehabilitations on a timely manner might lose an important opportunity to live a complete and healthy life. Eventually, the lack of hearing and speaking ability will affect the development of both mental and physical functions, intelligence, and social adaptability. Not only will this problem result in an irreparable regret to the hearing-impaired child for the life time, but also create a heavy burden for the family and society. Therefore, it is necessary to establish a set of computer-assisted predictive model that can accurately detect and help diagnose newborn hearing loss so that early interventions can be provided timely to eliminate waste of medical resources. This study uses information from the neonatal database of the case hospital as the subjects, adopting two different analysis methods of using support vector machine (SVM) for model predictions and using logistic regression to conduct factor screening prior to model predictions in SVM to examine the results. The results indicate that prediction accuracy is as high as 96.43% when the factors are screened and selected through logistic regression. Hence, the model constructed in this study will have real help in clinical diagnosis for the physicians and actually beneficial to the early interventions of newborn hearing impairment.

A Fast Sign Localization System Using Discriminative Color Invariant Segmentation

Building intelligent traffic guide systems has been an interesting subject recently. A good system should be able to observe all important visual information to be able to analyze the context of the scene. To do so, signs in general, and traffic signs in particular, are usually taken into account as they contain rich information to these systems. Therefore, many researchers have put an effort on sign recognition field. Sign localization or sign detection is the most important step in the sign recognition process. This step filters out non informative area in the scene, and locates candidates in later steps. In this paper, we apply a new approach in detecting sign locations using a new color invariant model. Experiments are carried out with different datasets introduced in other works where authors claimed the difficulty in detecting signs under unfavorable imaging conditions. Our method is simple, fast and most importantly it gives a high detection rate in locating signs.