A frame-based approach for capturing semantics from Arabic text for text-to-sign language MT

This paper describes the design and implementation of a computational model for Arabic natural language semantics, a semantic parser for capturing the deep semantic representation of Arabic text. The parser represents a major part of an Interlingua-based machine translation system for translating Arabic text into Sign Language. The parser follows a frame-based analysis to capture the overall meaning of Arabic text into a formal representation suitable for NLP applications that need for deep semantics representation, such as language generation and machine translation. We will show the representational power of this theory for the semantic analysis of texts in Arabic, a language which differs substantially from English in several ways. We will also show that the integration of WordNet and FrameNet in a single unified knowledge resource can improve disambiguation accuracy. Furthermore, we will propose a rule based algorithm to generate an equivalent Arabic FrameNet, using a lexical resource alignment of FrameNet1.3 LUs and WordNet3.0 synsets for English Language. A pilot study of motion and location verbs was carried out in order to test our system. Our corpus is made up of more than 2000 Arabic sentences in the domain of motion events collected from Algerian first level educational Arabic books and other relevant Arabic corpora.     

Effect of stepped‐impedance resonators on rectangular metamaterial unit cells

In this article, effect of the stepped‐impedance resonator (SIR) miniaturization technique on rectangular metamaterial unit cells is investigated and the influence of the method's structural parameters on the characteristic impedance and the distance between higher resonance modes is discussed. According to the results, the ideal unit cell for this method should be thick enough and have an impedance ratio greater than one. Furthermore, the SIR technique is applied on a conventional two‐turn spiral metamaterial unit cell and a new compact spiral unit cell is introduced. The effect of this method on the unit cell parameters is investigated and the new unit cell is compared to the conventional spiral. According to the results, a miniaturization factor of 0.75 can be achieved with the new unit cell. To validate the results, a two dimensional array of the unit cell is fabricated and its S‐parameters are measured using the free space method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:582–590, 2015.     

Using I2P (Invisible Internet Protocol) Encrypted Virtual Tunnels for a Secure and Anonymous Communication in VANets: I2P Vehicular Protocol (IVP)

Wireless Personal Communications - The Invisible Internet Project (I2P) as a secure protocol uses robust mechanisms and strong algorithms to reinforce the security and the anonymity of the...     

Ultra‐wideband slot antenna for wireless communication systems

In this article, a new ultra‐wideband rectangular‐slot antenna is proposed and developed for multiband wireless communication systems. The radiating slot is fed by a microstrip line with a microstrip fork‐shaped tuning stub. The frequency characteristic and radiation performance of the proposed antenna are successfully optimized, and a prototype is fabricated and tested. The measured results show that the impedance bandwidth can cover the band from 1.85 to 6.1 GHz with return loss of better than 10 dB, and the corresponding radiation displays omnidirectional patterns across the interested bands. With these frequencies, the proposed structure is especially suitable for applications in wireless communication systems, where a single antenna is needed to operate simultaneously at different bands, such as PCS (1.85–1.99 GHz), UMTS (1.92–2.17 GHz) and all WLAN bands (2.4–2.48 GHz and IEEE802.11a WLAN applications at 5.15–5.35 GHz and 5.725–5.825 GHz). © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2006.     

Biological treatment of industrial wastes in a photobioreactor.

An algal-bacterial consortium was tested for the treatment from a coke factory. A Chlorella vulgaris strain and a phenol-degrading Alcaligenes sp. were first isolated from the wastewater treatment plant to serve as inocula in the subsequent biodegradation tests. Batch tests were then conducted with samples from the real wastewater or using a synthetic wastewater containing 325 mg phenol/l and 500 mg NH4+/l as target pollutants. Direct biological treatment of the real wastewater was not possible due to the toxicity of organic compounds. Activated carbon adsorption and UV(A-B)-irradiation were efficient in detoxifying the effluent for subsequent biological treatment as inoculation of pretreated samples with the algal-bacterial consortium was followed by complete phenol removal and NH4+ removal of 45%. Complete phenol removal and 33% NH4+ removal were achieved during the fed-batch treatment of artificial wastewater at 6 d hydraulic retention time (HRT). Under continuous feeding at 3.6 d HRT, phenol and NH4+ removal dropped to 58 and 18%, respectively. However, complete phenol removal and 29% NH4+ removal were achieved when 8 g NaHCO3/l was added to the artificial wastewater to enhance algal growth. This study confirms the potential of solar-based industrial wastewater treatment based on solar-based UV pretreatment followed by algal-bacterial biodegradation.     

Crystallization of P Type Amorphous Silicon (a-Si: H) by AIC Method: Effect of Aluminum Thickness

In this work, we will study the crystallization of P type hydrogenated amorphous silicon (a-Si:H) by Aluminum Induced Crystallization technique (CIA) by varying the thickness of the aluminum films. We have deposited a 100 nm thickness of p-type a-Si:H layer on Corning glass substrates using PECVD technique. An aluminum layer with thickness ranging from 10 to 400 nm was thermally evaporated on the a-Si:H surface. The thermal annealing was performed in a conventional furnace at temperature of 550 °C for 4 h in flowing N2 ambient. The study of the crystallization of the Al/a-Si:H/Glass structure according the aluminum thickness was carried out by using Raman spectroscopy, X-rays diffraction and Hall Effect measurements. Raman results reveal the presence of the peaks between 510 and 520 cm−1, which are close to the peak of crystallized Si (about 521 cm−1) proving the crystallization of all samples. The XRD measurements show the presence of the characteristic peaks of the crystalline silicon, thus the a-Si: H (p) layer was effectively crystallized by the AIC method in a short time. Through Hall measurements we found an improvement in electrical properties and an increase in dopant concentration (+ 5.3 1014 to + 2.9 1017 cm2).     

An improved extreme learning machine model for the prediction of human scenarios in smart homes

One of the main objectives of smart homes is healthcare monitoring and assistance, especially for elderly and disabled people. Therefore, an accurate prediction of the inhabitant behavior is very helpful to provide the required assistance. This work aims to propose a prediction model that satisfies the accuracy as well as the rapidity of the learning phase. To do so, we propose to improve the existing extreme learning machine (ELM) model by defining a recurrent form. This form ensures a temporal relationship of inputs between observations at different time steps. The new model uses feedback connections to the input layer from the output layer which allows the output to be included in the long-term prediction. A recurrent dynamic network, with feedback connections of the output of the network, is proposed to predict the future series representing future activities of the inhabitant. The resulting model, called Recurrent Extreme Learning Machine (RELM), provides the ability to learn the human behavior and ensures a good balance between the learning time and the prediction accuracy. The input data is based on the real data representing the activities of persons belonging to the profile of first level (i.e. P ₁) as measured by the dependency model called Functional Autonomy Measurement System (SMAF) used in the geriatric domain. The experimental results reveal that the proposed RELM model requires a minimum time during the learning phase with a better performance compared to existing models.