Publications Scientifiques
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Item Chemical Composition and Antibacterial Activity of Lippia multiflora Moldenke Essential Oil from Different Regions of Angola(2020) Nsevolo, Samba; Aitfella Lahlou, Radhia; Mpazu, Nelo; Lucia, Silva; Rui, Coca; Rocha, Pedro; Jesus Miguel, López RodillaThe purpose of the study was to determine the chemical composition and antibacterialactivity ofLippia multifloraMoldenke essential oils (EOs) collected in different regions of Angola.Antibacterial activity was evaluated using the agar wells technique and vapour phase test. Analysisof the oils by GC/MS identified thirty-five components representing 67.5 to 100% of the totaloils. Monoterpene hydrocarbons were the most prevalent compounds, followed by oxygenatedmonoterpenes. The content of the compounds varied according to the samples. The main componentswere Limonene, Piperitenone, Neral, Citral, Elemol, p-cymene, Transtagetone, and Artemisia ketone.Only one of the eleven samples contained Verbenone as the majority compound. In the vapour phasetest, a single oil was the most effective against all the pathogens studied. The principal componentanalysis (PCA) and hierarchical cluster analysis (HCA) of components of the selected EOs andinhibition zone diameter values of agar wells technique allowed us to identify a variability betweenthe plants from the two provinces, but also intraspecific variability between sub-groups within apopulation. Each group of essential oils constituted a chemotype responsible for their bacterialinhibition capacity. The results presented here suggest that AngolanLippia multifloraMoldenke hasantibacterial properties and could be a potential source of antimicrobial agents for the pharmaceuticaland food industryItem Fault detection in a grid-connected photovoltaic system using adaptive thresholding method(Elsevier, 2018) Ammiche, Mustapha; Kouadri, Abdelmalek; Halabi, Laith M.; Guichi, Amar; Mekhilef, SaadIn this paper, an adaptive monitoring scheme with Fuzzy Logic Filter (FLF) is developed and applied to monitor a Grid-Connected Photovoltaic System (GCPVS). This method is based on Principal Component Analysis (PCA) and Moving Window Principal Component Analysis (MWPCA). It is designed to generate adaptive thresholds for its monitoring indices. The FLF filters the monitoring indices to reduce the number of False Alarms (FA) and increase the Fault Detection Rate (FDR). The application is carried out on the GCPVS of the Power Electronics and Renewable Energy Research Laboratory (PEARL) of Malaya University. The proposed technique is compared against PCA method in terms of FAR reduction. The detection ability of the adaptive thresholding with FLF monitoring scheme is tested first on simulated faults then it is applied to detect a real abnormal behaviour. The results show that the proposed method is effective in reducing the number of false alarms and in detecting different types of faults with high accuracyItem Combustion study of phoenicicole biomass in Algerian oasis using thermogravimetric analysis : deglet nour cultivar case(Springer, 2018) Bousdira, Khalida; Bousdira, Dina; Bekkouche, Sidi Mohammed El Amine; Yahiaoui, Fatma Zohra; Nouri, L’Hadi; Legrand, JackItem Importance of eyes and eyebrows for face recognition system(IEEE, 2015) Radji, Nadjet; Cherifi, Dalila; Azrar, ArabItem Importance of eyes and eyebrows for face recognition system(IEEE, 2015) Radji, Nadjet; Cherifi, Dalila; Azrar, Arab,,CTItem Impact of thatcher effect, double illusion and inversion on face recognition(IEEE, 2015) Radji, Nadjet; Cherifi, Dalila; Azrar, ArabItem Fusion of face recognition methods at score level(IEEE, 2017) Cherifi, Dalila; Cherfaoui, Fateh; Yacini, Si Nabil; Nait-Ali, AmineItem Effect of eyes and eyebrows on face recognition system performance(IEEE, 2014) Radji, N.; Cherifi, Dalila; Azrar, A.