Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

Mechanical and dynamic mechanical properties of jute fibers–Novolac–epoxy composite laminates

A study was done of jute composite using a polymer matrix of epoxidized Novolac resin (ENR), diglycidyl ether of bisphenol A (DGEBA)–based epoxy, and their blends with different weight percentages of the resins. It was found that on blending ENR with DGEBA, the storage modulii at room temperature are enhanced by about 100% or more in the case of 30 and 40% ENR‐containing matrices, whereas the enhancement in the case of 20 and 12% ENR‐containing matrices is only 50% that of the pure matrix. It was also observed that the tan δ peak heights of the composites containing 30 and 40% ENR are closer to that of 20% ENR‐containing composite. The probable explanation drawn on the basis of experimental findings of DMA and mechanical analysis is that by blending ENR with DGEBA epoxy it is possible to manufacture jute composites with increased stiffness without sacrificing their ductility. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2800–2807, 2002     

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.     

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.     

Non‐fragile reliable control synthesis of the sugarcane borer

This study considers the problem of non‐fragile reliable control synthesis for mathematical model of interaction between the sugarcane borer (Diatraea saccharalis) and its egg parasitoid Trichogramma galloi. In particular, the control could be substituted by periodic releases of a small population of natural enemies and hence it is important to propose the time‐varying controller in sugarcane borer. The main aim of this study is to design a state feedback non‐fragile (time‐varying) reliable controller such that the states of the sugarcane borer system reach the equilibrium point within the desired period. A novel approach is proposed to deal with the uncertain matrices which appear in non‐fragile reliable control. Finally, simulations based on sugarcane borer systems are conducted to illustrate the advantages and effectiveness of the proposed design technique. The result reveals that the proposed non‐fragile control provides good performance in spite of periodic releases of a small population of natural enemies occurs.Inspec keywords: microorganisms, plant diseases, biology computing, state feedback, biocontrol, control system synthesisOther keywords: nonfragile reliable control synthesis, sugarcane borer, mathematical model, Diatraea saccharalis, egg parasitoid, Trichogramma galloi, periodic releases, natural enemies, state feedback nonfragile time‐varying reliable controller, equilibrium point, design technique     

A self-configurable large-scale virtual manufacturing environment for collaborative designers

As manufacturing environments are getting distributed and increasing in size, the related virtual environments are getting larger and more closely networked together. This trend has led to a new paradigm—large-scale virtual manufacturing environment (LSVME). It supports networked and distributed virtual manufacturing to meet manufacturing system requirements. Since it contains a large number of virtual components, an effective data structure and collaborative construction methodology are needed. A metaearth architecture is proposed as the data structure for representing LSVME. This architecture consists of virtual space layer, mapping layer, library layer and ontology layers, which describe interaction among virtual components and has the ability to analyze the characteristics of virtual environment. In addition, it increases reusability of virtual components and supports self-reconfiguration for manufacturing simulation. A heuristic construction method based on graph theory is proposed using this architecture. It prevents redundant design of virtual components and contributes to an effective construction scheduling technique for collaborative designers.