Abstract: Nowadays, enormous amounts of accessible textual information available on the Internet are phenomenal. Automatic text classification is considered an important application in natural language processing. It is the process of assigning a document to predefined categories based on its content. In this paper, the well-known Centroid-based technique developed for text classification is considered to be applied on Arabic text. Arabic language is highly inflectional and derivational which makes text processing a complex and challenging task. In the proposed work, the Centroid-based Algorithm is adopted and adapted to be applied to classify Arabic documents. The implemented algorithm is evaluated using a corpus containing a set of Arabic documents. The experimental results against a dataset of 1400 Arabic text documents covering seven distinct categories reveal that the adapted Centroid-based algorithm is applicable to classify Arabic documents. The performance criteria of the implemented Arabic classifier achieved roughly figures of 90.7%, 87.1%, 88.9%, 94.8%, and 5.2% of Micro-averaging recall, precision, F measure, accuracy, and error rates respectively.

Abstract— Automatic text categorization is considered an important application in natural language processing. It is the process of assigning a document to predefined categories based on its content. In this research, some well-known techniques developed for classifying English text are considered to be applied on Arabic. This work focuses on applying the well-known Rocchio (Centroid-based) technique on Arabic documents. This technique uses centroids to define good class boundaries. The centroid of a class c is computed as center of mass of its members. Arabic language is highly inflectional and derivational which makes text processing a complex task. In the proposed work, first Arabic text is preprocessed using tokenization and stemming techniques. Then, the Rocchio Algorithm is adopted and adapted to be applied to classify Arabic documents. The implemented algorithm is evaluated using a corpus containing a set of actual documents. The results show that the adapted Rocchio algorithm is applicable to categorize Arabic text. Ratios of 92.2%, 92.7%, and 92.1% of Micro-averaging recall, precision, and F-measure respectively are achieved, against a data set of 500 Arabic text documents covering five distinct categories.

Network layer indications are not readily available upon a link change; therefore, general dependes on the network layer may introduce unnecessary delays due to network layer signaling for a simple link layer handover. If information could be gathered at link layer to determine the need for network layer signaling, then both the delay and signaling load could be really improved over the current standards of Mobile IP.

This paper presents a Cross-layer decision on two layer network and link layers to improve the performance of Enhanced Mobile IP (E-Mobile IP) handover in which reducing packet loss and latency during handover process.

Cutting samples (n = 93) from the Sirte, Tagrifet, Rakb, Rachmat, Bahi Formations of Upper Cretaceous and Nubian Formation (Lower Cretaceous) derived from eleven wells (6C1-59, 6J1-59, 6R1-59, KK1-65, OO2-65, M1-51, KK1-65, B-96, B-95, B-99, E1-NC-59) locate in the Amal, Gialo, Nafoora, and Sarir Fields present in East Sirte Basin were analysed in the aim of their organic geochemical evaluation. A bulk geochemical parameters and evaluation of specific biomarkers by chromatography-mass spectrometry (GC-MS) implemented to find out a diversity of interbedded non-marine lithofacies including sandstones, siltstones, shales and conglomerates. Such rocks are good source and contain fair to good contented of organic matter passing in the course of very good, in which the excellent source rocks have organic carbon richness (TOC) reached to 5.16 wt%. The studied samples are ranged from gas to oil-prone organic matter (OM) of hydrogen index (HI) ranged between 115 - 702 mg HC/g TOC, related with gas prone (OM) of (HI) <150 and most beds contain oil-prone organic matter of (HI) > 300, associated with oxygen index (OI): 3 - 309 mg CO2/g TOC indicate that organic matter is dominated by Type II/III kerogen. The maturity of these source rocks is variations ranges from mature to post-mature-oil window in the Sirte and Rachmat Formations, as inferred from the production index (PI: 0.07 - 1.55) and Tmax and Ro% data (Tmax: 425 - 440/Ro%: 0.46 - 1.38) and early to mid-stage maturities for the other formations. Low PI in some samples seems to imply that the most of the hydrocarbons have expelled and migrated from the rocks. Biomarker ratios of individual hydrocarbons in rock extracts (n = 21), were also used in order to investigate the samples’ thermal maturity and palaeo depositional conditions. Pristine/Phytane ratios of 0.65 - 1.25 and dibenzothiophene to phenanthrene (DBT/P) ratios of 0.04 - 0.47 indicated Anoxic and suboxic conditions of depositional source rock. The origin of OM of the studied samples attributed to a marine algal source as indicated from the dominated by the C27 and co-dominant C28 homologues sterane in molecular composition distributions. The marine shale and carbonate lithofacies of rock samples were also indicated by high C19TT/C23TT ratio and low relative abundance of C24TeT/C23TT, consistent with their interpreted marine affinity. An organic geochemical evaluation pointed out that the Sirte Shale formation (Campanian/Turonian) is the main source rock in this petroleum area. 

Tricyclic terpanes to hopanes Ratios calculated from individual biomarkers to delineate their distribution, identifications, mixing ratios and biological precursor in a suite of crude oils (n = 24) from the East Sirt Basin. Geochemical application of Tricyclic terpane and Hopane biomarkers is divided studied oils into five groups (I, II, III, IV and V) based on the different ratios between Tricyclic terpanes to hopanes. Percentages of C23 Tricyclic terpanes/17α (H), 21β(H)-hopanes (C30αβ) and C28 Tricyclic terpane/17α (H), 21β (H)-30 hopanes (C31) have divided crude oils into 2 main individual groups in addition to 3 mixed groups. Group I, characterized by the dominance and extension of the tricycle terpane series (≈ C45 Tricyclic terpane). Group V, distinguished with the dominance of 17α (H), 21β (H) hopanes series. Groups II, contained a domination Tricyclic terpanes and hopanes, considered as a mixed group. The group III demonstrated equivalent ratios of Tricyclic terpanes to hopanes. The Group IV revealed a reduced amount of Tricyclic terpanes with enrich of hopanes. Tricyclic terpanes derived from tricyclohexaprenol precursors and attributed to a marine depositional environment and algal matter. Hopanes in obtained from bacteriohopane polyols and aminopolyols and distinguished to a depositional bacterial environment.

 Abstract. We investigate harmonic Bergman spaces bp = bp(Ω), 0 < p < ∞, where Ω = Rn \Zn and prove that bq ⊂ bp for n/(k + 1) ≤ q < p < n/k. In the planar case we prove that bp is non empty for all 0 < p < ∞. Further, for each 0 < p < ∞ there is a non-trivial f ∈ bp tending to zero at infinity at any prescribed rate.

Abstract. We prove that ωu(δ) ≤ Cωf(δ), where u: Ω → Rn is the harmonic extension of a continuous map f: ∂Ω → Rn, if u is a K-quasiregular map and Ω is bounded in Rn with C2 boundary. Here C is a constant depending only on n, ωf and K and ωh denotes the modulus of continuity of h. We also prove a version of this result for Λω-extension domains with c-uniformly perfect boundary and quasiconformal mappings.

 In this paper, English language will be used as an instance of natural languages as we will be concerned with the set of all natural language texts. this research tries to employ a set of all synonyms as a way to hide secret message inside a natural language text.