Enhanced anti-biofilm activity of facile synthesized silver oxide nanoparticles against K. pneumoniae

Journal of Inorganic and Organometallic Polymers and Materials - The silver oxide nanoparticle was successfully synthesized using floral waste by simple one pot, cost effective method. The complete...     

Soft computing models based feature selection for TRUS prostate cancer image classification

Ultrasound imaging is the most suitable method for early detection of prostate cancer. It is very difficult to distinguish benign and malignant nature of the affliction in the early stage of cancer. This is reflected in the high percentage of unnecessary biopsies that are performed and many deaths caused by late detection or misdiagnosis. A computer based classification system can provide a second opinion to the radiologists. Generally, objects are described in terms of a set of measurable features in pattern recognition. The selection and quality of the features representing each pattern will have a considerable bearing on the success of subsequent pattern classification. Feature selection is a process of selecting the most wanted or dominating features set from the original features set in order to reduce the cost of data visualization and increasing classification efficiency and accuracy. The region of interest (ROI) is identified from transrectal ultrasound (TRUS) images using DBSCAN clustering with morphological operators after image enhancement using M3-filter. Then the 22 grey level co-occurrence matrix features are extracted from the ROIs. Soft computing model based feature selection algorithms genetic algorithm (GA), ant colony optimization (ACO) and QR are studied. In this paper, QR-ACO (hybridization of rough set based QR and ACO) and GA-ACO (hybridization GA and ACO) are proposed for reducing feature set in order to increase the accuracy and efficiency of the classification with regard to prostate cancer. The selected features may have the best discriminatory power for classifying prostate cancer based on TRUS images. Support vector machine is tailored for evaluation of the proposed feature selection methods through classification. Then, the comparative analysis is performed among these methods. Experimental results show that the proposed method QR-ACO produces significant results. Number of features selected using QR-ACO algorithm is minimal, is successful and has high detection accuracy.     

The use of a mixing-sensitive chemical reaction for the study of pulp fibre suspension mixing

The competitive, consecutive chemical reactions between 1-naphthol and diazotized sulfanilic acid were utilized to study the mixing of a pulp fibre suspension in a 22 L stirred tank reactor. Mixing quality was determined from the distribution between the mono and bis substituted reaction products once a correlation was made for the adsorption of the product dyes onto the suspended fibres. The technique was found to be adequate for assessing micromixing and turbulence intensity within a fibre suspension provided the measured product distribution, Xs, was between 0.4 and 0.01. Thus the mixing conditions that could be assessed depended on both the energy dissipation within the mixer and the amount of the fibre present. For the experimental conditions chosen for this study energy dissipation rates would typically have to be less than 80 W/kg and the suspension mass concentration less than 2.5%. When compared with water, a reduction in turbulence levels at both the impeller zone and a remote zone in the stirred vessel was observed for fibre mass concentrations as low as 0.5%. The turbulence decreased as the suspension mass concentration was increased. This decrease is attributed to energy dissipation by friction at fibre-fibre contact points as the fibres move relative to one another in the flow. This sink removes energy from the turbulence cascade which never shows up as small-scale fluid deformations leading to better mixing.     

Synthesis and characterization of liquid crystalline polymers containing aromatic ester mesogen and a nonmesogenic ferrocene unit in the spacer

A new series of liquid crystalline polymers containing aromatic triad ester mesogen and 1,1′‐disubstituted ferrocene as a nonmesogenic unit along with polymethylene spacer was synthesized. The polymer was synthesized by a room temperature polycondensation reaction between bis(4‐chloroformyl phenyloxy alkyl ferrocene dicarboxylate) and quinol. The alkyl groups have been varied by an even number of methylene groups with a range from two to ten groups. All the polymers were found to possess liquid crystalline properties. The identification of the mesophase is more transparent with an increase in the spacer. The thermal characteristics were studied using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The results reveal that the thermal stability of the polymers was decreased with increasing spacer length. The T_g, T_m, and T_i of the polymers decreased with increasing methylene groups. The incorporation of the ferrocene moiety also has a considerable effect on the glass transition temperature. The char yield of the polymer decreases with an increasing methylene chain length. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3494–3501, 2002     

Genetic based sensorless hybrid intelligent controller for strip loop formation control between inter-stands in hot steel rolling mills

Safe operating environment is essential for all complex industrial processes. The safety issues in steel rolling mill when the hot strip passes through consecutive mill stands have been considered in this paper. Formation of sag in strip is a common problem in the rolling process. The excessive sag can lead to scrap runs and damage to machinery. Conventional controllers for mill actuation system are based on a rolling model. The factors like rise in temperature, aging, wear and tear are not taken into account while designing a conventional controller. Therefore, the conventional controller cannot yield a requisite controlled output. In this paper, a new Genetic-neuro-fuzzy hybrid controller without tension sensor has been proposed to optimize the quantum of excessive sag and reduce it. The performance of the proposed controller has been compared with the performance of fuzzy logic controller, Neuro-fuzzy controller and conventional controller with the help of data collected from the plant. The simulation results depict that the proposed controller has superior performance than the other controllers.     

A Hybrid RF and Vision Aware Fusion Scheme for Multi-Sensor Wireless Capsule Endoscopic Localization

A huge torrent of data traffic is generated from various heterogeneous applications and services at the Internet backbone. In general, at the backbone, all such applications and services are allocated spectral resources under a shared spectrum environment within elastic optical networks (EONs). In such a fully shared environment, connection requests (CRs) belonging to different traffic profiles compete for spectral resources. Hence, it is very challenging for network operators to resolve resource conflict that occur at the time of provisioning resources to such CRs. The heterogeneous traffic profile (HTP) considered in this work includes permanent lightpath demands (PLDs) and scheduled lightpath demands (SLDs). We propose various distance adaptive routing and spectrum assignment (DA-RSA) heuristics to resolve resource conflict among these two traffic profiles in EONs under a full sharing environment. Conventionally, preemption was the only technique to resolve such resource conflict among HTPs. Since preemption involves the overhead of selecting CRs to be preempted and then deallocating the resources given to those CRs, excessive preemption adversely affects the performance of the network. Therefore, in this work, we utilized bandwidth splitting as a solution to resolve resource conflict among HTPs under such a shared environment in EONs. Moreover, an integrated solution consisting of splitting and preemption is also proposed. We refer to this new integration as flow-based preemption. Our simulation results demonstrate that bandwidth splitting-based heuristics yield significant improvement in terms of the amount of bandwidth accepted in the network, link and node utilization ratio, number of transponders utilized and the amount of bandwidth dropped due to preemption. Moreover, the flow-based preemption approach is proved to be superior in performance amongst all proposed strategies.

     

Encrypted Network Traffic Classification and Resource Allocation with Deep Learning in Software Defined Network

Wireless Personal Communications - The climate has changed absolutely in every area in just a few years as digitized, making high-speed internet service a significant need in the future. Future...     

Organometallic L-Alanine Cadmium Iodide Crystals for Optical Device Fabrication

Single crystals of L-alanine cadmium iodide (LACI) were grown by the slow evaporation technique at room temperature. A single-crystal X-ray diffraction (SXRD) model was used to evaluate the crystal structure of the as-grown LACI crystal. The energy dispersive X-ray (EDX) analysis and ultraviolet-visible-near infrared (UV-vis-NIR) transmittance studies were carried out, and the results reveal the presence of elements in the title compound. From the transmittance data, the optical bandgap as a function of photon energy was estimated, and the different optical constants were calculated. A fluorescence study was performed for the LACI crystal. Thermogravimetric and differential thermal analyses have also been studied to investigate the thermal property of the LACI crystal. The efficiency of the second harmonic generation (SHG) of the title crystal was investigated. The magnetic and electrical properties were estimated by the vibrating sample magnetometer (VSM) analysis and impedance study, respectively.