Speech recognition system based on Hidden Markov Model concerning the Moroccan dialect DARIJA

In this work, we present a system for automatic speech recognition on the Moroccan dialect. We used the hidden Markov model to model the phonetic units corresponding to words taken from the training base. The results obtained are very encouraging given the size of the training set and the number of people taken to the registration. To demonstrate the flexibility of the hidden Markov model we conducted a comparison of results obtained by the latter and dynamic programming

Yield gaps and nutrients use efficiency of apple tree (golden delicious/MM106) in the middle Atlas Mountains of Morocco

The main objective of this work was to evaluate use efficiency of nitrogen, phosphorus, potassium, calcium and magnesium in adult apple orchards in the Middle Atlas of Morocco and to establish preliminary reference norms for fertilizing this crop under local conditions. The study was based on soil and leaf analysis and data with regard to farming practices and yield on forty apple orchards (cv. Golden delecious/MM106) where nineteen are growing on silty-clay soil and twenty-one on sandy-loam soil. The results showed significant correlations between leaf content for each nutrient and yield level following polynomial equations, thereby indicating local reference norms for apple leaf analysis. Moreover, correlations were significant between leaf and soil contents that permitted to determine apple needs in nitrogen fertilizer and references norms for soil richness in phosphorus, potassium, calcium and magnesium to obtain yield potential in the study region. However, the found norms are less than International standards because of feebleness of yield level in the study region, largely related to deficient cultural practices adopted by farmers. In addition, investigation of leaf nutrients ratios N/K, N/Ca, K/Ca, K/Mg and Ca/Mg showed that there was disharmony in uptake of these nutrients originating particularly from high soil richness in Ca and Mg. Taking into account these considerations, the found references norms can be applied only under the adopted farming practices. Nevertheless, by improving local practices, reference values may change

3D-QSAR modeling, Molecular Docking and drug-like properties investigations of novel heterocyclic compounds derived from Magnolia Officinalis as Hit Compounds against NSCLC

In this work, we used the CoMSIA approach to develop a 3D-QSAR model for describing the quantitative structure-activity relationship of 51 novel compounds derived from Magnolia officinalis as potential agents against non-small cell lung cancer. The CoMSIA model developed with steric (S), electrostatic (E), hydrophobic (H), donor and acceptor hydrogen bonds (D and A) showed high efficiency in predicting pIC50 activity (R² = 0.81; Q² = 0.51; R2pred= 0.80, SEE=0.03). The predictions of the developed 3D-QSAR model were supported by a molecular docking simulation that was performed on the highest biologically active molecule in the series of molecules studied. In addition, novel molecules designed on the basis of the structural properties predicted by the CoMSIA model and molecular docking studies. In silico drug-like evaluation of novel designed molecules indicated the suitability of compounds T1, T2 and T3 for use as future drugs for the treatment of non-small cell lung cancer. Therefore, the three proposed molecular structures could be adopted as key in the development of new drugs that inhibit lung cancer cell lines by targeting the EGFR tyrosine kinase

Système de reconnaissance automatique de la parole Amazigh à base de la transcription en alphabet Tifinagh

Dans ce travail, nous présentons un système de reconnaissance automatique de la parole Amazigh basé sur la transcription en alphabet Tifinagh reconnue par l’Institut Royal de la Culture Amazigh (IRCAM ). Nous avons utilisé le modèle de Markov caché et on a fait une comparaison avec la méthode de programmation dynamique

Structuring communities for sharing human digital memories in a social P2P network

A community is sub-network inside P2P networks that partition the network into groups of similar peers to improve performance by reducing network traffic and high search query success rate. Large communities are common in online social networks than traditional file-sharing P2P networks because many people capture huge amounts of data through their lives. This increases the number of hosts bearing similar data in the network and hence increases the size of communities. This article presents a Memory Thread-based Communities for our Entity-based social P2P network that partition the network into groups of peers sharing data belonging to an entity–person, place, object or interest, having its own digital memory or be a part another memory. These connected peers having further similarities by organizing the network using linear orderings. A Memory-Thread is the collection of digital memories having a common reference key and organized according to some form of correlation. The simulation results show an increase in network performance for the proposed scheme along with a decrease in network overhead and higher query success rate compared to other similar schemes. The network maintains its performance even while the network traffic and size increase

Partial regularity and t-analytic sets for Banach function algebras

In this note we introduce the notion of t-analytic sets. Using this concept, we construct a class of closed prime ideals in Banach function algebras and discuss some problems related to Alling’s conjecture in H infinity. A description of all closed t-analytic sets for the disk-algebra is given. Moreover, we show that some of the assertions in [8] concerning the O-analyticity and S-regularity of certain Banach function algebras are not correct. We also determine the largest set on which a Douglas algebra is pointwise regular