Preparation of hydrophilic dimethyl 5‐sodium sulfoisophthalate/poly(ethylene terephthalate) nanofiber composite membranes for improving antifouling properties

In this study, the effect of dimethyl 5‐sodium sulfoisophthalate (SSI) nanoparticles (NPs) on the antifouling properties of poly(ethylene terephthalate) (PET) electrospun nanofiber membranes (ENMs) was investigated through the ultrafiltration of C. I. Basic Blue 3. 3 dye. To reveal the tortuous effect of this additive on the antifouling properties, scanning electron microscopy was used for the characterization of the ENM structure and the optimization of the SSI NP content. Then, some selected physical and structural properties of the membrane, such as the porosity, moisture regain, contact angle, hydraulic permeability (L _p ), and mechanical properties, in the optimized range of SSI NP contents were investigated. Finally, the influence of this additive on the rejection and flux recovery ratio of the prepared membranes was considered. Consequently, the antifouling properties were assessed with consideration of all of the aforementioned parameters. The SSI/PET2 membrane (that with 0.02% w/w SSI NPs with respect to the total amount of PET polymer and SSI NPs), with an average nanofiber diameter of 450 nm, a porosity of 78.44%, a moisture regain of 9.34%, a contact angle of 86.48°, an L _p of 42,167 L h^?1 m^?2 bar^?1, a tensile strength of 4.66 ± 0.04 MPa, a flux recovery ratio of 15.3%, and a final rejection of 95%, showed a significant enhancement in the antifouling properties compared with pristine PET ENMs. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134 , 44522.     

Regionalization of Rainfall Intensity-Duration-Frequency using a Simple Scaling Model

Design storm is one of the most important tools to design hydraulic structures, hydrologic system and watershed management, mostly extracted by intensity- duration - frequency (IDF) curves for a given specific duration and return period. As for conventional methods to calculate IDF curves, the precipitation should be recorded for different durations so that foregoing curves can be extracted. Such data can be collected from rain gauge stations. In many areas, just daily precipitation data are available by which IDF curves cannot be extracted as per conventional methods. The aim of this research is to make IDF curves for short-term durations according to time scaling model as well as daily rainfalls. The relationships of this method are characterized with three variables including mean (μ ₂₄) and standard deviation (σ ₂₄) of daily rainfall intensity, and scaling exponent (H) by which all IDF curves might be drawn. The method used in present paper entails for less computational steps than conventional methods and by far has low parameters considerably than others in turn increases reliability. Scaling method is used to extract the IDF curves in rain-gauge stations in Khuzestan province located in southwest Iran and results proved the efficiency and robustness of the scaling method. Also ability of scaling concept method was examined in constructing of regional IDF.     

A mathematical exploitation of simulated uniform scanning botnet propagation dynamics for early stage detection and management

The contribution of this paper is two-fold. Firstly, we propose a botnet detection approach that is sufficiently timely to enable a containment of the botnet outbreak in a supervised network. Secondly, we show that mathematical models of botnet propagation dynamics are a viable means of achieving that level of defense from bot infections in a supervised network. Our approach is built on the idea of processing network traffic such as to localize a weakly connected subgraph within a graph that models network communications between hosts, and thus consider that subgraph as representative of a suspected botnet. We devise applied statistics to infer the propagation dynamics that would characterize the suspected botnet if this latter were indeed a botnet. The inferred dynamics are materialized into a model graph. A subgraph isomorphism search determines whether or not there is an approximate match between the model graph and any subgraph of the weakly connected subgraph. An approximate match between the two leads to a timely identification of infected hosts. We have implemented this research in the Matlab and Perl programming languages, and have validated it in practice in the Emulab network testbed. In the paper, we describe our approach in detail, and discuss experiments along with experimental data that are indicative of the effectiveness of our approach.     

Clustering botnet communication traffic based on n-gram feature selection

Recognized as one the most serious security threats on current Internet infrastructure, botnets can not only be implemented by existing well known applications, e.g. IRC, HTTP, or Peer-to-Peer, but also can be constructed by unknown or creative applications, which makes the botnet detection a challenging problem. Previous attempts for detecting botnets are mostly to examine traffic content for bot command on selected network links or by setting up honeypots. Traffic content, however, can be encrypted with the evolution of botnet, and as a result leading to a fail of content based detection approaches. In this paper, we address this issue and propose a new approach for detecting and clustering botnet traffic on large-scale network application communities, in which we first classify the network traffic into different applications by using traffic payload signatures, and then a novel decision tree model is used to classify those traffic to be unknown by the payload content (e.g. encrypted traffic) into known application communities where network traffic is clustered based on n-gram features selected and extracted from the content of network flows in order to differentiate the malicious botnet traffic created by bots from normal traffic generated by human beings on each specific application. We evaluate our approach with seven different traffic trace collected on three different network links and results show the proposed approach successfully detects two IRC botnet traffic traces with a high detection rate and an acceptable low false alarm rate.     

People tracking using a network-based PTZ camera

In this paper, we propose a method for online upper body tracking using an IP PTZ camera. This type of camera uses a built-in Web server resulting in variable response times when sending control commands. Furthermore, communicating with a Web server involves network delays. Thus, because the camera is inside a control loop, the effective frame rate that can be processed by a computer vision method is irregular and in general low (2–6 fps). Our tracking method has been specifically designed to perform in such conditions. It detects, at every frame, candidate blobs using motion detection, region sampling, and region color appearance. The target is detected among candidate blobs using a fuzzy classifier. Then, a movement command is sent to the camera using the target position and speed. The proposed method can cope with low frame rate, and thus with large motion of the target, even in the case of a fast walk. Results show that our system has a good target detection precision (>88%) and low track fragmentation, and the target is almost always localized within 1/6th of the image diagonal from the image center.     

Grafting of water‐soluble sulfonated monomers onto functionalized fumed silica nanoparticles via surface‐initiated redox polymerization in aqueous medium

Sulfonated polymer/fumed silica hybrid nanoparticles were prepared via surface‐initiated free radical polymerization of 2‐acrylamido‐2‐methyl‐1‐propane sulfonic acid (PAMPS‐g‐FSN), styrene sulfonic acid sodium salt (PSSA‐g‐FSN) and vinyl sulfonic acid sodium salt (PVSA‐g‐FSN) from the surface of aminopropyl‐functionalized fumed silica nanoparticles (AFSNs) dispersed in aqueous medium. Cerium(IV) ammonium nitrate/nitric acid and sodium dodecyl sulfate were used as redox initiator and stabilizer respectively. AFSNs were prepared by covalently attaching 3‐aminopropyltriethoxysilane onto the surface of fumed silica nanoparticles. Sulfonated monomers (AMPS, SSA or VSA) were then grafted onto the AFSNs ultrasonically dispersed in water via redox initiation at 40 °C. Structure, thermal properties, particle size and morphology of the AFSNs and PAMPS‐g‐FSN, PSSA‐g‐FSN and PVSA‐g‐FSN hybrid nanoparticles were characterized by Fourier transform infrared spectroscopy, TGA, SEM, transmission electron microscopy (TEM) and dynamic light scattering (DLS). The results indicated that the sulfonated monomers were successfully grafted onto the fumed silica nanoparticles. Grafting amounts of the sulfonated polymers onto the fumed silica nanoparticle surface were estimated from TGA thermograms to be 59%, 13% and 29% for the PAMPS, PSSA and PVSA, respectively. From SEM, TEM and DLS analysis, polymer‐grafted fumed silica nanoparticles with an average diameter smaller than 70 nm and a (semi‐) spherical shape were observed. A significant bimodal particle size distribution was observed only for the PAMPS‐g‐FSN with average diameters of 39.6 nm (84.1% per number) and 106 nm (15.9% per number). The hydrophilic sulfonated polymer/grafted fumed silica obtained from the redox graft polymerization gave a stable colloidal dispersion in acidic aqueous medium. Copyright © 2012 Society of Chemical Industry     

Inclined-plane tracking and erosion test according to the IEC 60587 Standard

The present IEC 60587 IEC standard needs several improvements which would help manufacturers of power equipment and material suppliers to assess outdoor polymeric materials in a more reliable way.