Inverse active networks

Inverse networks are defined. `Inverse active network theorem? is stated and proved. A few applications of this theorem are illustrated.     

Solar map of India under clear sky conditions

This paper focusses on generation of solar irradiation map under clear sky conditions using r.sun model. Direct Irradiation, diffuse irradiation and global irradiation maps are plotted using programme which was developed in C language. This programme calculates different components of solar irradiation using clear sky model (r.sun). Further Surfer software was used to plot different irradiation maps. All three values (Direct Irradiation, Global Irradiation and Diffuse Irradiation) were compared by IMD values for performing statistical analysis i.e. Mean Bias Error (MBE), Root Mean Square Error (RMSE) and standard deviation. MBE was found within ±10%, RMSE lies within <20% and standard deviation was found to have very low value which indicated good fitting between model results and calculated values. Therefore the r.sun model is good model and can be used for computing solar irradiation for India.     

Creep performance of CNT reinforced glass fiber/epoxy composites: Roles of temperature and stress

Carbon nanotubes (CNTs) have been emerged as a potential nanofiller to reinforce polymeric materials to improve their mechanical properties, like strength and modulus. However, time-dependent deformation of such materials under a constant load and elevated temperature is a matter of concern for long-term durability of these materials. The present article primarily demonstrates the effects of creep temperature and stress on the reinforcement efficiency of CNT in a glass fiber/epoxy (GE) composite. Two types of materials were investigated in this study—GE which was used as a control material, as well as CNT embedded GE composite. To elucidate the impact of CNT on the long-term durability of GE composite, creep tests have been performed at different temperatures (50, 80, and 110 °C) under bending loading. As applied stress has also significant contribution toward the elevated creep deformation of materials, creep tests have also been carried out under different stresses (5, 10, and 40 MPa). The strength of the CNT-GE composite exhibited 8.7 and 18.3% higher than that of control GE composite under tensile and bending load, respectively. Results suggest CNT reinforcement to be beneficial for low temperature applications, both in terms of creep strain and strain rate. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47674.     

Effect of a predetection open segment in the column on speed and selectivity in capillary electrochromatography

Columns in capillary electrochromatography (CEC) most commonly have the detection window located immediately after the retaining frit of the packed segment. Here, the properties of "duplex" columns having a predetection open segment between the frit and the detector window are examined with particular regard to the effect of the relative lengths of the packed and open segments on the separation of mixtures containing neutral and charged components. This configuration allows the use of columns with short packed segments in contemporary instruments for rapid separations. It is shown that, by varying the length of the packed segment, the balance of chromatographic and electrophoretic forces can be shifted, and the selectivity can be adjusted if the separation involves the interplay of both mechanisms. Expressions are presented for estimating the retention time in a duplex column if the chromatographic and electrophoretic properties of the sample components are known. The results are expected to facilitate CEC method development in selection of the respective column segment lengths for optimum separation.     

M-IDM: A Multi-Classification Based Intrusion Detection Model in Healthcare IoT

In recent years, the application of a smart city in the healthcare sector via loT systems has continued to grow exponentially and various advanced network intrusions have emerged since these loT devices are being connected. Previous studies focused on security threat detection and blocking technologies that rely on testbed data obtained from a single medical IoT device or simulation using a well-known dataset, such as the NSL-KDD dataset. However, such approaches do not reflect the features that exist in real medical scenarios, leading to failure in potential threat detection. To address this problem, we proposed a novel intrusion classification architecture known as a Multi-class Classification based Intrusion Detection Model (M-IDM), which typically relies on data collected by real devices and the use of convolutional neural networks (i.e., it exhibits better performance compared with conventional machine learning algorithms, such as naïve Bayes, support vector machine (SVM)). Unlike existing studies, the proposed architecture employs the actual healthcare IoT environment of National Cancer Center in South Korea and actual network data from real medical devices, such as a patient’s monitors (i.e., electrocardiogram and thermometers). The proposed architecture classifies the data into multiple classes: Critical, informal, major, and minor, for intrusion detection. Further, we experimentally evaluated and compared its performance with those of other conventional machine learning algorithms, including naïve Bayes, SVM, and logistic regression, using neural networks.     

Exploiting encrypted and tunneled multimedia calls in high-speed big data environment

Due to the rapid increase in the speed as well as the number of users over the Internet, the rate of data generation is enormously grown. In addition, at the same rate, the multimedia transmission especially the usage of VoIP calls is rapidly growing due to its cost effectiveness, dramatic functionality over the traditional telephone network and its compatibility with public switched telephone network (PSTN). In most of the developing countries, internet service providers (ISPs) and telecommunication authorities are concerned in detecting such calls to either block or prioritize commercial VoIP. Signature-based, port-based, and pattern-based detection techniques are inaccurate due to the complex and confidential security and tunneling mechanisms used by VoIP. Therefore, in this paper, we proposed a generic, robust, efficient statistical analysis-based solution to identify encrypted and tunneled voice media flows. We extracted six statistical parameters, which are extracted for each flow and compared with threshold values while generating a number of rules to identify VoIP media calls. The paper also offers a complete architecture that can efficiently process high-speed traffic in order to detect VoIP flows at real-time. The proposed system, including the architecture and the algorithm, can be practically implemented in a real environment, such as ISP or telecommunication authority’s gateway. We implemented the system using the parallel environment of Hadoop ecosystem with Spark on the top of it to achieve the real-time processing. We evaluated the system by considering 1) the accuracy in terms of detection rate by computing the direct rate and false positive rate and 2) the efficiency in terms of processing power. The result shows that the system has 97.54% direct rate and .00015% false positive rate, which are quite high. The comparative study proved that the proposed system is more accurate than the existing techniques.

     

Visible‐light‐induced controlled/living radical polymerization of styrene with a phenyl seleno group at one terminal chain end: 1‐(Phenylseleno)ethyl benzene as a photoiniferter

The photopolymerization of styrene with a well‐defined molecular architecture and a low polydispersity index and with methyl and phenylseleno (? SePh) groups at α‐ and ω‐chain ends, respectively, was performed via a controlled/living radical polymerization with a new initiating system, 1‐(phenylseleno)ethyl benzene/tert‐butyl diphenyl (phenylseleno) silane, through the absorption of visible light at room temperature. A novel initiating living radical polymerization was examined. The yield and number‐average molecular weight (M_n) of the resulting polymer increased with the reaction time. Furthermore, a linear relationship was found in a plot of M_n versus the polymer yield. These results indicated that this polymerization proceeded through a living radical mechanism. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 348–355, 2004     

Increase of catalyst utilization in polymer electrolyte membrane fuel cells by shape-selected Pt nanoparticles

In the present work, we succeeded in supporting predominantly cuboctahedral Pt nanoparticles onto high surface area carbons while maintaining their shape. These novel catalysts were applied in a realistic fuel cell set-up for the first time and showed remarkable fuel cell performance. A 95% fraction of cuboctahedral Pt nanoparticles was synthesized using tetradecyltrimethylammonium bromide (TTAB) as a stabilizer. Transmission electron micrographs of the synthesized samples demonstrated the presence of monodispersed cuboctahedral particles of 12 nm in size. Cyclic voltammetry (CV) studies of the unsupported cuboctahedral nanoparticles revealed the presence of Pt (110) and (100) facets. The shape-selected Pt nanoparticles were let to absorb onto Vulcan carbon by a simple dispersing procedure to obtain supported shape-selected Pt nanoparticles. Only by this gentle adsorption step of the surfactant-stabilized nanoparticles on the carbonaceous support material, the nanoparticles retained their shape. Finally an MEA was fabricated using the supported shape-selected nanoparticles and tested in a realistic H₂-PEM fuel cell environment. In terms of Pt utilization, shape-selected Pt particles were found to be more effective by a factor of four in weight compared to the commercial catalyst.     

Towards a super-resolution based approach for improved face recognition in low resolution environment

Multimedia Tools and Applications - The video surveillance activity generates a vast amount of data, which can be processed to detect miscreants. The task of identifying and recognizing an object...