Effect of cellulose acetate/cellulose triacetate ratio on reverse osmosis blend membrane performance

Surface functionalization and modification including the grafting process are effective approaches to improve and enhance the reverse osmosis (RO) membrane performance. This work is aimed to synthesize grafted/crosslinked cellulose acetate (CA)/cellulose triacetate (CTA) blend RO membranes using N-isopropylacrylamide (N-IPAAm) as a monomer and N,N-methylene bisacrylamide (MBAAm) as a crosslinker. The morphology of these membranes was analyzed by scanning electron microscopy and their surface roughness was characterized by atomic force microscopy. The performance of these membranes was evaluated through measuring two major parameters of salt rejection and water flux using RO unit at variable operating pressures. It was noted that the surface average roughness obviously decreased from 148 nm for the pure CA/CTA blend membrane with 2.5% CTA to 110 nm and 87 nm for the grafted N-IPAAm and grafted/crosslinked N-IPAAM/MBAAm/CA/CTA-RO membranes, respectively. Moreover, the contact angle decreased from 51.98° to 47.6° and 43.8° after the grafting and crosslinking process. The salt rejection of the grafted CA/CTA-RO membrane by 0.1% N-IPAAm produced the highest value of 98.12% and the water flux was 3.29 L/m²h at 10 bar.     

Molecular characterization of erythrocyte glucose-6-phosphate dehydrogenase deficiency in Al-Ain District, United Arab Emirates

Operational skills involved in controlling a motor vehicle were measured in two groups of very healthy elderly drivers and a young control group to test the hypothesis that there are age-related declines in operational performance that may influence driver safety. An actual behind-the-wheel, standardized road test was employed using a motor vehicle equipped with sensors to record speed, braking activity, and lane position, as well as direction and magnitude of front-wheel and eye-movement excursions. The data from these sensors were used as dependent measures of operational performance. Older drivers made fewer steering and eye-movement excursions and drifted across the center line more frequently than the young control group. Younger drivers drove significantly faster and executed more braking applications than did their older counterparts. The motor-vehicle operational performance of older healthy drivers was related to visual-spatial attentional declines and the useful field of vision associated with the normal aging process.     

Multi-criteria Decision-making Approach for Environmental Impact Assessment to Reduce the Adverse Effects Of Dams

Water Resources Management - Environmental Impact Assessments (EIAs) of development projects are necessary to minimize negative impacts and maximize benefits. The objective of this paper is to...     

Edge Computing Platform with Efficient Migration Scheme for 5G/6G Networks

Next-generation cellular networks are expected to provide users with innovative gigabits and terabits per second speeds and achieve ultra-high reliability, availability, and ultra-low latency. The requirements of such networks are the main challenges that can be handled using a range of recent technologies, including multi-access edge computing (MEC), artificial intelligence (AI), millimeter-wave communications (mmWave), and software-defined networking. Many aspects and design challenges associated with the MEC-based 5G/6G networks should be solved to ensure the required quality of service (QoS). This article considers developing a complex MEC structure for fifth and sixth-generation (5G/6G) cellular networks. Furthermore, we propose a seamless migration technique for complex edge computing structures. The developed migration scheme enables services to adapt to the required load on the radio channels. The proposed algorithm is analyzed for various use cases, and a test bench has been developed to emulate the operator’s infrastructure. The obtained results are introduced and discussed.     

Dynamic and scalable multi-level trust management model for Social Internet of Things

The Internet of Things (IoT) is a paradigm that has made everyday objects intelligent by offering them the ability to connect to the Internet and communicate. Integrating the social component into IoT gave rise to the Social Internet of Things (SIoT), which has helped overcome various issues such as heterogeneity and navigability. In this kind of environment, participants compete to offer a variety of attractive services. Nevertheless, some of them resort to malicious behaviour to spread poor-quality services. They perform so-called Trust-Attacks and break the basic functionality of the system. Trust management mechanisms aim to counter these attacks and provide the user with an estimate of the trust degree they can place in other users, thus ensuring reliable and qualified exchanges and interactions. Several works in literature have interfered with this problem and have proposed different Trust-Models. The majority tried to adapt and reapply Trust-Models designed for common social networks or peer-to-peer ones. That is, despite the similarities between these types of networks, SIoT ones present specific peculiarities. In SIoT, users, devices and services are collaborating. Devices entities can present constrained computing and storage capabilities, and their number can reach some millions. The resulting network is complex, constrained and highly dynamic, and the attacks-implications can be more significant. In this paper, we propose DSL-STM a new dynamic and scalable multi-level Trust-Model, specifically designed for SIoT environments. We propose multidimensional metrics to describe and SIoT entities behaviours. The latter are aggregated via a Machine Learning-based method, allowing classifying users, detecting attack types and countering them. Finally, a hybrid propagation method is suggested to spread trust values in the network, while minimizing resource consumption and preserving scalability and dynamism. Experimentation made on various simulated scenarios allows us to prove the resilience and performance of DSL-STM.

     

Throughput analysis of STS-based CDMA system with variable spreading factor in non-frequency selective Rayleigh fading channel

The throughput enhancement of space-time spreading (STS)-based code division multiple access (CDMA) system is investigated in this paper. Variable spreading factor (VSF) is utilized to improve the data throughput of the system in non-frequency selective Rayleigh fading channel. In this contribution, an analytical approach is proposed to compute a new expression for the bit error rate (BER) performance of the STS-based CDMA system against pre-despreading signal-to-noise-ratio (SNR) for different values of spreading factor. The other contribution of the paper is deriving a new analytical expression for the throughput enhancement of the VSF STS-based CDMA system in non-frequency selective Rayleigh fading channel. Simulation and analytical results demonstrate that using VSF method in STS-based CDMA system improves the throughput of the system by keeping the BER performance at a target level.     

Knowledge Based Supervised Fuzzy-Classification: An Application to Image Processing

In this paper, we take an interest in representation and treatment of imprecision and uncertainty in order to propose an original approach to approximate reasoning. This work has a practical application in supervised learning pattern recognition. Production rules whose conclusions are accompanied by belief degrees, are obtained by supervised learning from a training set. The proposed learning method is multi-featured, it allows to take into account the possible predictive power of a simultaneously considered feature conjunction. On the other hand, the feature space partition allows a fuzzy representation of the features and data imprecision integration. This uncertainty is managed in the learning phase as well as in the recognition one. To introduce more flexibility and to overcome the boundary problem due to the manipulations of membership functions of fuzzy sets, we propose to use a context-oriented approximate reasoning. For this purpose, we introduce an adequate distance to compare neighbouring facts. This distance, measuring imprecision, combined with the uncertainty of classification decisions represented by belief degrees, drives the approximate inference. The proposed method was implemented in a software called SUCRAGE and confronted with a real application in the field of image processing. The obtained results are very satisfactory. They validate our approach and allow us to consider other application fields.     

A systematic approach to integrate common timed security rules within a TEFSM-based system specification

Context

Formal methods are very useful in the software industry and are becoming of paramount importance in practical engineering techniques. They involve the design and modeling of various system aspects expressed usually through different paradigms. These different formalisms make the verification of global developed systems more difficult.

Objective

In this paper, we propose to combine two modeling formalisms, in order to express both functional and security timed requirements of a system to obtain all the requirements expressed in a unique formalism.

Method

First, the system behavior is specified according to its functional requirements using Timed Extended Finite State Machine (TEFSM) formalism. Second, this model is augmented by applying a set of dedicated algorithms to integrate timed security requirements specified in Nomad language. This language is adapted to express security properties such as permissions, prohibitions and obligations with time considerations.

Results

The proposed algorithms produce a global TEFSM specification of the system that includes both its functional and security timed requirements.

Conclusion

It is concluded that it is possible to merge several requirement aspects described with different formalisms into a global specification that can be used for several purposes such as code generation, specification correctness proof, model checking or automatic test generation. In this paper, we applied our approach to a France Telecom Travel service to demonstrate its scalability and feasibility.     

Physiological and biochemical markers in the process of resistance and/or tolerance of heavy metals in the abandoned mining area of Sidi Kamber,Skikda, Algeria

This paper reports the biomonitoring of metallic pollution in the mine of Sidi Kamber Skikda town, to determine the resistance and/or tolerance to Zn, Pb, Cd and Cu in metalliferous plants. During the period of March–May, 2015, soil and plants samples were collected from three different stations in the study area. The total heavy metal fraction was determined by ICP/MS, whereas biochemical markers were determined by spectrophotometric techniques. The results obtained showed high levels of heavy metals in soil and plants compared to international standards. The translocation factor revealed that the studied plants can transfer and/or accumulate metals in their roots or their aerial parts as a function of characteristics of each metal, soil contents and physiological role in the plant. The contents of chlorophyll, proline, total sugars and total proteins are directly influenced by changes in bioavailable contents of heavy metals. It has been found that the plants studied and biomarkers are better suited for phytoremediation and biomonitoring of heavy metals pollution.     

Nonlinear multi-scale decomposition by EMD for Co-Channel speaker identification

Multimedia Tools and Applications - A multi-scale analysis method, called Empirical Mode Decomposition (EMD), has been proposed for analysis of nonlinear and non stationary data. The empirical mode...