Combining Dictionary and Web-mined Resources for Arabic-English Cross Language Information Retrieval

In cross-language information retrieval (CLIR), queries in a source language are used to retrieve relevant documents in a target language. Dictionary-based translation is a traditional approach used by cross-language information retrieval systems. However, it has bad performance when queries contain words that do not appear in the dictionary (Out Of Vocabulary -OOV). Combinations of resources such as dictionaries and Web mining techniques can play an important role in solving these problems. In this research we propose incorporating Machine Readable Dictionaries (MRD) and Web mining techniques. Previous work and experimentation in other language pairs such as Chinese-English showed that OOV can be effectively alleviated using these techniques. This project is therefore adapting these techniques to Arabic-English CLIR

Current Approaches in Arabic IR: A Survey

Arabic information retrieval is a popular area of research. This paper presents the current state-of-the-art in Arabic Information Retreival (IR) approaches. Moreover, it provides general guidance for open research areas and future directions

Identification of Proteus Mirabilis on Banknotes Using 16s rRNA gene in Khartoum State

Background: The presence of pathogenic bacteria in circulated currency was recorded as a public health hazard. In this study, all examined Sudanese banknotes (100%) were found to be contaminated by gram-negative bacteria. Proteus mirabilis were recovered from 10 examined notes (22.2%, f = 10), E. coli (13.3%, f = 6) and Klebsiella spp. (8.9%, f = 4) were also identified. Only the most resistant P. mirabilis isolate was identified using culture-based and 16S rRNA gene sequencing techniques. Methods: Proteus isolates were identified phenotypically and tested for their susceptibility to 16 of commonly used antibiotics, then most resistant isolate was confirmed genotypically via 16S rRNA gene amplification and sequencing. Bioinformatics analysis using BLAST for sequence similarity search, Clustal W program for multiple sequence alignment, MEGA7 software for phylogenetic analysis. Tree was constructed to show the evolutionary relationships of the obtained sequencewith similar sequences in the databases using. Results: The obtained sequence was found to be 100% identical to P. mirabilis 16S rRNA gene using BLAST. The phylogenetic tree was constructed to show the evolutionary relationships of the obtained sequence with similar sequences in the databases using MEGA7 software, and the closest strain was found to be P. mirabilis strain from India (EU411047) Conclusion: This study has shown that some currency notes circulated at Khartoum transportation are carriers of antimicrobial-resistant P. mirabilis that could be potential source for their transmission in public

Learning Behavior of Memristor-Based Neuromorphic Circuits in the Presence of Radiation

In this paper, a feed-forward spiking neural network with memristive synapses is designed to learn a spatio-temporal pattern representing the 25-pixel character ‘B’ by separating correlated and uncorrelated afferents. The network uses spike-timing-dependent plasticity (STDP) learning behavior, which is implemented using biphasic neuron spikes. A TiO2 memristor non-linear drift model is used to simulate synaptic behavior in the neuromorphic circuit. The network uses a many-to-one topology with 25 pre-synaptic neurons (afferent) each connected to a memristive synapse and one post-synaptic neuron. The memristor model is modified to include the experimentally observed effect of state-altering radiation. During the learning process, irradiation of the memristors alters their conductance state, and the effect on circuit learning behavior is determined. Radiation is observed to generally increase the synaptic weight of the memristive devices, making the network connections more conductive and less stable. However, the network appears to relearn the pattern when radiation ceases but does take longer to resolve the correlation and pattern. Network recovery time is proportional to flux, intensity, and duration of the radiation. Further, at lower but continuous radiation exposure, (flux 1x1010 cm−2 s−1 and below), the circuit resolves the pattern successfully for up to 100 s

A New High Yielding and Long Staple Egyptian Cotton (Gossypium barbadense L.) Variety "Super Giza 94"

The Egyptian long staple cotton variety "Super Giza 94" was developed by Cotton Research Institute CRI, Giza, Egypt, which belongs to Gossypium barbadense L. Super Giza 94 is a novel plant structure improved seed cotton yield, lint percentage and fiber quality traits. Super Giza 94 was developed through one-way hybridization of elite parental cotton genotypes accompanied by pedigree selection method to incorporate the excellent combinations of higher yield potential, early maturity and fiber quality traits with resistance to Fusarium wilt. The superior plant combinations were selected in F2-F6 generations entirely based on phenotypic plant traits and progeny yield potential in the field conditions. The selected strains were evaluated in multilocations yield trials over three years and six locations in a randomized complete block design with six replications. The results of these trials exhibited that the new variety surpassed the three commercial varieties of these locations in most yield traits. Super Giza 94 is characterized by early maturity with high yield potential, fluffy opening and easy to pick, strong resistance to Fusarium wilt disease, high lint percentage (40.2%) with improved fiber traits including fiber length (34.1mm), fiber strength (43.4 g/tex), micronaire reading (4.2), uniformity ratio (86.9%), yellowness +b (8.3), brightness Rd (79.8%) and white lint color. Super Giza 94 can solve maximum challenges of better cotton production in the area and fulfill industrial requisitions. For that, recommended for general cultivation in the Delta region in the 2016 growing season