Experiencing flow with instant messaging and its facilitating role on creative behaviors

The goal of this study is to explore how experiencing flow with IM, an Internet-based communication technology, can facilitate an individual’s perception on creativity. We argue that certain capabilities in IM, telepresence and perceived control, provide users a means to experience flow. We further investigate whether flow and its outcomes, positive affect and exploratory behavior have any influence on the perception of creativity of the users. Using an online survey with 207 observations we found that user’s perceived control over the technology and its ability to transport the user to a virtual environment were shown to facilitate the experience of flow. We found that flow in itself does not influence perceived expected creativity in its users but does indirectly influence perceived expected creativity through exploratory behavior and positive affect. From these initial findings we believe that our study provides implications for both users and designers on IT. Furthermore, managers can apply the findings during implementation and use of interactive information technologies for communications in the workplace.     

Prediction of tensile strength of friction stir welded aluminium matrix TiCp particulate reinforced composite

The usage of particulate reinforced metal matrix composite (MMC) is steadily increasing due to its properties such as high specific strength, high specific modulus and good wear resistance. Aluminium matrix composite (AMC) plays an important role to meet the above requirements. Effective utilization of AMC is based on not only its production but also on fabrication methods. Among AMCs, those based on particulate reinforcements are particularly attractive, due to their lower production costs. Aluminium matrix titanium carbide reinforced composite (Al–TiC_p) was produced in an inert atmosphere by indigenously developed Modified Stir Casting Process with bottom pouring arrangement (3–7% TiC by weight). Friction stir welding process (FSW) is employed to make weld joints. The welding parameters such as axial force, welding speed, tool rotational speed, percentage TiC addition etc., and profile of the tool were considered for analysis. In this study, an attempt is made to predict ultimate tensile strength (UTS) of the welded joints using a mathematical model. The FSW specimens without any post-weld heat treatment belonging to a different set of parameters tested, exhibited a high joint efficiency (most of them ranging from 90% to 98%) with respect to the ultimate tensile strength of the base material AA6061. It was found from the analysis of the model that the tool pin profile and the welding speed have more significant effect on tensile strength.     

Detecting Streaming of Twitter Spam Using Hybrid Method

Twitter, the social network which evolving faster and regular usage by millions of people and who become addicted to it. So spam playing a major role for Twitter users to distract them and grab their attention over them. Spammers actually detailed like who send unwanted and irrelevant messages or websites and promote them to several users. To overcome the problem many researchers proposed some ideas using some machine learning algorithms to detect the spammers. In this research work, a new hybrid approach is proposed to detect the streaming of Twitter spam in a real-time using the combination of a Decision tree, Particle Swarm Optimization and Genetic algorithm. Twitter has given access to the researchers to get tweets from its Twitter-API for real-time streaming of tweet data which they can get direct access to public tweets. Here 600 million tweets are created by using URL based security tool and further some features are extracted for representation of tweets in real-time detection of spam. In addition, our research results are compared with other hybrid algorithms which a better detection rate is given by our proposed work.     

Design and Characterization of a W-Band Folded-Waveguide Slow-Wave Structure

A single-section slow-wave structure for a W-band folded-waveguide traveling-wave tube with operating bandwidth of around 4% was designed for delivering the output power of 50 W at the operating voltage of 13.5 kV and operating beam current of 80 mA. The design was carried out using analytical formulations and 3D electromagnetic simulations. The beam-wave interaction analysis was carried out using large signal Lagrangian analysis and particle-in-cell simulation. The folded-waveguide slow-wave structure along with input-output couplers and RF windows were fabricated. Cold test measurements were carried out for dispersion characteristics of the slow-wave structure and voltage standing-wave ratio and insertion loss characteristics of the RF window. The measured cold circuit parameters show close agreement with the analysis.     

Cluster head selection for energy efficient and delay-less routing in wireless sensor network

Wireless sensor network (WSN) is comprised of tiny, cheap and power-efficient sensor nodes which effectively transmit data to the base station. The main challenge of WSN is the distance, energy and time delay. The power resource of the sensor node is a non-rechargeable battery. Here the greater the distance between the nodes, higher the energy consumption. For having the effective transmission of data with less energy, the cluster-head approach is used. It is well known that the time delay is directly proportional to the distance between the nodes and the base station. The cluster head is selected in such a way that it is spatially closer enough to the base station as well as the sensor nodes. So, the time delay can be substantially reduced. This, in turn, the transmission speed of the data packets can be increased. Firefly algorithm is developed for maximizing the energy efficiency of network and lifetime of nodes by selecting the cluster head optimally. In this paper firefly with cyclic randomization is proposed for selecting the best cluster head. The network performance is increased in this method when compared to the other conventional algorithms.

     

A unified framework for tree search decoding: rediscovering the sequential decoder

We consider receiver design for coded transmission over linear Gaussian channels. We restrict ourselves to the class of lattice codes and formulate the joint detection and decoding problem as a closest lattice point search (CLPS). Here, a tree search framework for solving the CLPS is adopted. In our framework, the CLPS algorithm is decomposed into the preprocessing and tree search stages. The role of the preprocessing stage is to expose the tree structure in a form matched to the search stage. We argue that the forward and feedback (matrix) filters of the minimum mean-square error decision feedback equalizer (MMSE-DFE) are instrumental for solving the joint detection and decoding problem in a single search stage. It is further shown that MMSE-DFE filtering allows for solving underdetermined linear systems and using lattice reduction methods to diminish complexity, at the expense of a marginal performance loss. For the search stage, we present a generic method, based on the branch and bound (BB) algorithm, and show that it encompasses all existing sphere decoders as special cases. The proposed generic algorithm further allows for an interesting classification of tree search decoders, sheds more light on the structural properties of all known sphere decoders, and inspires the design of more efficient decoders. In particular, an efficient decoding algorithm that resembles the well-known Fano sequential decoder is identified. The excellent performance-complexity tradeoff achieved by the proposed MMSE-DFE Fano decoder is established via simulation results and analytical arguments in several multiple-input multiple-output (MIMO) and intersymbol interference (ISI) scenarios.     

A novel prognosis and segmentation of necrosis (dead cells) in contrast enhanced T1-weighted glioblastoma tumor with automatic contextual clustering

In recent years, mortality rate with high-grade tumor has been increased significantly especially with glioblastoma (GBM) brain tumor while compared to other malignant brain tumor. Here, the amount of dead cells accommodated with the tumor tissue in GBM brain tumor play a vital task and necessitate an earlier diagnosis of malignancy with the GBM tumor. It inspires to implement new automatic diagnosis system which detects the dead cells and tumor tissue with the GBM brain tumor, such that the survival rate of the diseased can easily be prognosis by the Radiologist and Neurosurgeon. The main objective of this article is to detect the amount of dead cells with respect to tumor tissue associated with the GBM brain tumor which desires the impact factor of the brain tumor. In this framework, initially, the new contrast enhancement modality is incorporated to enhance the gray information over the dead cells and the tumor tissue with the T1-weighted MRI GBM brain tumor. In this enhancement, the edges of the tumor cells and its dead cells are magnified efficiently. As the noises and outliers with MR image is unpredictable and it experiences the variable amount of noises over the local window, the contextual information over each pixel of the image is adaptively modified with respect to the amount of noise over local window using adaptive contextual clustering. The performance evaluation of the framework is investigated which exhibits the overwhelming result compared to conventional detection techniques.     

An optimization study for preventing silica gelation and improving filtration effectiveness during pH reduction of high concentration silica solutions

The steam generation processes at the steam-assisted gravity drainage facilities result in huge quantities of wastewater streams, which are characterized by high pH and high silica levels. These concentrated streams need to be neutralized before their disposal via down-hole injection. The neutralization of these high-pH brines results in the formation of a gel-like substance, which makes it difficult to filter the amorphous silica gel. The wastewater used in this study was synthetically prepared using sodium metasilicate to mimic high-concentration silica solutions. Our experiments did not show any advantage of a two-step pH-neutralization process over the single-step process for suppressing silica gelation. A systematic experimental campaign was undertaken to investigate the effects of SiO₂ concentration, NaCl:SiO₂ ratio, and pH on the residual silica concentration, percent silica removal, filtration rate, and filtration effectiveness. For NaCl:SiO₂ ratios higher than 4.5, silica precipitation during pH reduction did not lead to the formation of gel or sol. The response surface methodology (RSM), based on the Doehlert design of experiments, was implemented to optimize the responses and provide high efficacy with fewer experiments. The results from the analysis of variance (ANOVA) analyses of the experimental data were used to evaluate the significance of each term in the quadratic model. 3D response surfaces and 2D contour plots were generated for determining the optimal ranges of independent factors for achieving the maximum silica removal, the highest filtration rate, the best filtration effectiveness, and the minimum residual silica concentration. An optimum operating region was established from the RSM analysis and overlay plot.     

Antimicrobial and anticoagulation activity of silver nanoparticles synthesized from the culture supernatant of Pseudomonas aeruginosa

Here, we describe biosynthesis of silver nanoparticles by reduction of aqueous Ag⁺ ions with the culture supernatant of Pseudomonas aeruginosa. The morphological, physiological, biochemical and molecular level identification of the strain GS1 resembles P. aeruginosa. The nanoparticles synthesized by P. aeruginosa were characterized by UV–vis spectroscopy, dynamic light scattering (DLS) and scanning electron microscopy (SEM). The size-distribution of nanoparticles was determined using a particle-size analyzer and the average particle-size was found to be 80 nm. The biological activities of the synthesized silver nanoparticles like antimicrobial activity were confirmed against Escherichia coli and Staphylococcus aureus and it have stable anti-coagulant effect.