CPU load prediction using neuro-fuzzy and Bayesian inferences

Ensuring adequate use of the computing resources for highly fluctuating availability in multi-user computational environments requires effective prediction models, which play a key role in achieving application performance for large-scale distributed applications. Predicting the processor availability for scheduling a new process or task in a distributed environment is a basic problem that arises in many important contexts. The present paper aims at developing a model for single-step-ahead CPU load prediction that can be used to predict the future CPU load in a dynamic environment. Our prediction model is based on the control of multiple Local Adaptive Network-based Fuzzy Inference Systems Predictors (LAPs) via the Naïve Bayesian Network inference between clusters states of CPU load time points obtained by the C-means clustering process. Experimental results show that our model performs better and has less overhead than other approaches reported in the literature.     

QRS detection based on wavelet coefficients

Electrocardiogram (ECG) signal processing and analysis provide crucial information about functional status of the heart. The QRS complex represents the most important component within the ECG signal. Its detection is the first step of all kinds of automatic feature extraction. QRS detector must be able to detect a large number of different QRS morphologies. This paper examines the use of wavelet detail coefficients for the accurate detection of different QRS morphologies in ECG. Our method is based on the power spectrum of QRS complexes in different energy levels since it differs from normal beats to abnormal ones. This property is used to discriminate between true beats (normal and abnormal) and false beats. Significant performance enhancement is observed when the proposed approach is tested with the MIT-BIH arrhythmia database (MITDB). The obtained results show a sensitivity of 99.64% and a positive predictivity of 99.82%.     

Coupling of electrodialysis and leaching processes for removing of cadmium from phosphate ore

Phosphate rock is a valuable material that is used for the production of large phosphorus chemicals. However, this natural material usually contains some toxic elements such as cadmium (Cd). Cd is a non-nutritive metal regarded as harmful to both humans and the environment. The main toxic effects of Cd on human health are the kidney and renal cortex diseases. Other effects were observed on pulmonary, cardiovascular, and musculoskeletal systems, in addition to including Cd as a human carcinogen. In order to reduce the cadmium content in the phosphate ore, an original method was studied and consists of coupling both leaching and electrodialysis. The effects of process parameters, such as reaction time, nature, and concentration of the extracting agent, liquid/phosphate ore ratio, pH, temperature, and current density, were investigated. The obtained results show that the cadmium extraction from phosphate ore using simple batch leaching does not reduce the cadmium content to the required level. However, the application of leaching- electrodialysis coupled method at optimum current density of 10 mA cm^?2 increases the cadmium extraction efficiency up to 84.3%. This synergetic process could be applied to the treatment of phosphate ore containing cadmium.     

Antioxidant abietane diterpenoids from Salvia barrelieri

The root extract of endemic Algerian Salvia species Salvia barrelieri Ettling and its diterpenoids were investigated for potential antioxidant activity. From its acetone extract, a new natural abietane diterpenoid 7-oxoroyleanone-12-methyl ether (1) and six known diterpenoids 7α-acetoxyroyleanone-12-methyl ether (2), royleanone (3), horminone (4), 7-acetylhorminone (5), cryptojaponol (6) and inuroyleanol (7) were isolated, and their structures were elucidated by spectroscopic means. Among the diterpenoids, the new diterpenoid 7-oxoroyleanone-12-methyl ether (1) showed highest superoxide anion scavenging activity while inuroyleanol (7) showed both the highest 1,1-diphenyl-2-picrylhydrazyl (DPPH) scavenging activity and inhibition of lipid peroxidation in β-carotene–linoleic acid system. These findings indicate that S. barrelieri extract as well as isolated abietane diterpenes, particularly inuroyleanol are promising antioxidants which can be used as food additives.     

Erythrocyte Toxicities of Imidazolidinyl Urea and Diazolidinyl Urea

The addition of antimicrobial preservatives to pharmaceutical and cosmetic products is necessary to prevent microbial growth. However, the use of preservatives can also produce other undesirable effects. For several years, researchers have been investigating the use of alternative methods in safety assessment of cosmetic ingredients and formulations by means of variety methods. The aim of this study was to evaluate the erythrocyte toxicities of two commercial preservatives： imidazolidinyl urea and diazolidinyl urea. Relatively few studies about the cytotoxicity of these preservative are available. The determination of their cytotoxicity is an essential step to warrant their safe use. Erythrocyte toxicities were evaluated by assessment of the amount of hemoglobin released by red blood cells after their lysis. In this study, both imidazolidinyl urea and diazolidinyl urea showed cytotoxic activity against red blood cells. The imidazolidinyl urea induce a small release of hemoglobin after 120 min of incubation. But, the diazolidinyl urea induce a massive release of hemoglobin from the imidazolidinyl urea （a rate of 83% at concentrations of 6.25 mg/mL and 12.5 mg/mL）.     

Phenolic composition and antioxidant capacities of ten Algerian date (Phoenix dactylifera L.) cultivars: A comparative study

Phenolic compounds and antioxidant capacities of ten Algerian date (Phoenix dactylifera L.) cultivars were investigated. The total phenolic, flavonoid, flavonol and condensed tannin contents of the different cultivars were measured using colorimetric methods. Free phenolic acid and flavonoid profiles of the date cultivars were analyzed by high performance liquid chromatography with diode array detection (HPLC-DAD), while antioxidant capacities were evaluated in vitro using scavenging assays of 1,1-diphenyl-2-picrylhydrazyl radical and hydrogen peroxide, ferric reducing power, and ferrous ion chelating ability. The results showed that the cultivars exerted different antioxidant capacities, and had different phenolic acid and flavonoid patterns. Among the tested cultivars, Ghazi, Arechti and Sebt Mira possessed the strongest antioxidant capacities and the highest phenolic contents. Four phenolic acids (gallic, ferulic, coumaric and caffeic acids) and five flavonoids (isoquercetrin, quercetrin, rutin, quercetin and luteolin) were identified and quantified.     

Novel mullite-cordierite ceramic refractory fabricated from halloysite and talc

This research work aims to fabricate industrial refractory bricks using cheap and abundant kaolin DD₃ constituted of Halloysite. The fabrication process consists on mixing the crushed raw materials (Kaolin/Clay, Fireclay, Talc) with the respective proportions and an optimized granulometry, shaped by a uniaxial hydrostatic pressure of 250 bars, followed by drying at 100°C and sintering at 1300°C. The addition of Talc - at first with water, Fireclay and AP/DD₃- as a source of MgO promotes the increase of Cordierite formation in order to obtain high heat resistance shock and reduced thermal expansion. Three assays are studied with AP Clay and DD₃ Kaolin weight ratios (100/0, 50/50 and 0/100) % corresponding to (ER₀, ER₁ and ER₂) respectively. Mineralogical analysis results of the new refractory bricks, indicate the presence of Mullite and Cordierite as major phases besides Corundum and Quartz as minor phases. All products (ER₀, ER₁ and ER₂) are found to be argillaceous refractory with Alumina concentration (40 < Al₂O₃ < 45%, FC 40 group) and a melting point higher than 1600°C. The mechanical resistance of the samples is of the same order of magnitude; reaching 51 MPa.     

Medee Method Framework: a situational approach for organization-centered MAS

This paper presents a situational approach, called Medee Method Framework, which allows the development of organization-centered MAS in a disciplined way, even though some agent organizational (AO) models are not currently incorporated into agent-oriented software engineering (AOSE) methods. In order to do that, such a method framework proposes the composition of MAS situational methods out of method fragments according to a given project situation, by applying the principles proposed by situational method engineering. The proposed approach provides a high degree of reuse and flexibility, allowing the composition of new methods as well as the reengineering of AOSE methods based on the standards proposed by SPEM. Furthermore, it allows the user to leverage advantages of both AOSE methods and AO models in order to develop organization-centered MAS. The Medee Method Framework offers a method repository that covers different development phases, such as requirements, analysis, design, implementation, as well as the main components of a MAS application, like agents, environments, interactions, and organizations. This repository has been sourced from several AOSE methods and AO models, as Gaia, Tropos, Ingenias, PASSI, MOISE, and OperA.     

Automatic identification of knowledge-transforming content in argument essays developed from multiple sources

Developing knowledge-transforming skills in writing may help students increase learning by actively building knowledge, regardless of the domain. However, many undergraduate students struggle to transform knowledge when drafting essays based on multiple sources. Writing analytics can be used to scaffold knowledge transforming as writers bring evidence to bear in supporting claims. We investigated how to automatically identify sentences representing knowledge transformation in argumentative essays. A synthesis of cognitive theories of writing and Bloom's typology identified 22 linguistic features to model processes of knowledge transforming in a corpus of 38 undergraduates' essays. Findings indicate undergraduates mostly paraphrase or copy information from multiple sources rather than engage deeply with sources' content. Eight linguistic features were important for discriminating evidential sentences as telling versus transforming source knowledge. We trained a machine learning algorithm that accurately classified nearly three of four evidential sentences as knowledge-telling or knowledge-transforming, offering potential for use in future research.