Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

Energy savings are very common in IoT sensor networks because IoT sensor nodes operate with their own limited battery. The data transmission in the IoT sensor nodes is very costly and consume much of the energy while the energy usage for data processing is considerably lower. There are several energy-saving strategies and principles, mainly dedicated to reducing the transmission of data. Therefore, with minimizing data transfers in IoT sensor networks, can conserve a considerable amount of energy. In this research, a Compression-Based Data Reduction (CBDR) technique was suggested which works in the level of IoT sensor nodes. The CBDR includes two stages of compression, a lossy SAX Quantization stage which reduces the dynamic range of the

         Aceclofenac (AC) is an orally active phenyl acetic acid derivative, non-steroidal anti-inflammatory drug with exceptional anti-inflammatory, analgesic and antipyretic properties. It has low aqueous solubility, leading to slow dissolution, low permeability and inadequate bioavailability. The aim of the current study was to prepare and characterize AC-NS-based gel to enhance the dissolution rate and then percutaneous permeability. NS.s were prepared using solvent/antisovent precipitation method at different drug to polymer ratios (1:1, 1:2, and 1:3) using different polymers such as poly vinyl pyrrolidone (PVP-K25), hydroxy propyl methyl cellulose (HPMC-E5) and poloxamer® (388) as stabilizer

By- products of corn starch industry were used to prepare media for propagation the lactic acid bacteria as a natural auxotroph. The by- products used were the corn steep water (S) and gluten extract (G) after a proper treatment to get them ready for media preparation. The results showed that it was possible to replace the peptone and meat extract by gluten extract in MRS medium. The growth was approximately similar to that obtained in standard MRS media. Corn steep water (S) was used as well and the growth enhanced by including Tween – 80 at 1% level. The later media named MZ, which was superior for growing standard and local strains and starters. The MZ medium modified by adding acetate and glacial acetic acid similarly to

in this worl three types of complexed phenolic resins were prepared using various additives such as and improving the aim of this work higher mechanical properties this work is done

Single mode-no core-single mode fiber structure with a section of tuned no-core fiber diameter to sense changes in relative humidity has been experimentally demonstrated. The sensor performance with tuned NCF diameter was investigated to maximize the evanescent fields. Different tuned diameters of of (100, 80, and 60)μm were obtained by chemical etching process based on hydrofluoric acid immersion. The highest wavelength sensitivity was obtained 184.57 pm/RH% in the RH range of 30% –100% when the no-core fiber diameter diameter was 60 μm and the sensor response was in real-time measurements

Abstract

The fiber Bragg grating (FBG) technology has been rapidly applied in the sensing technology field. In this work, uniform FBG was used as pressure sensor based on measuring related Bragg wavelength shift. The pressure was applied directly by air compressor to the sensor and the pressure was ranged from 1 to 6 bar.

      This sensor also was affected by the external temperature so as a result it could be used as a temperature sensor. This sensor could be used to monitor the pressure of dams. It has been shown from the result that the sensor is very sensitive to the pressure and the sensitivity was (67 pm\bar) and is very sensitive to temperature and the sensitivity was (10p