Study of polyaniline polyacrylamide composites by positron annihilation technique

Polyaniline doped with nonoxidizing Bronsted acids is recognized as a conducting material, as its electrical conductivity changes with percentage of doping. In the present work, different percentages of doped polyaniline were blended with polyacrylamide and their electrical conductivities as well as the positron annihilation lifetimes were measured. Analysis of data yielded three lifetime components. It was observed that the value of the short lifetime component remained constant for doping concentration, whereas that of the intermediate component τ₂ decreased. The relative intensity pertaining to τ₂, however, increased with the increase in doped PANI concentration. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 930–933, 2003     

Topography of the flank wear surface

In many applications, topography represents the main external features of a surface. This paper describes the topography of the flank wear surface and also presents the relationship between the maximum flank wear and the topography parameters (roughness parameters) of the flank wear surface during the turning operation. A modern CNC lathe machine (Okuma LH35-N) was used for the machine turning operation. Three-dimensional surface roughness parameters of the flank wear surface were measured by a surface texture instrument (from Talysurf series) using surface topography software (Talymap). Based on the resulting experimental data, it is found that as the flank wear increases, the roughness parameters (sR_a, sR_q, and sR_t) on the flank surface increase significantly. The greater the roughness value of the flank wear surface, the higher the friction of the tool on the workpiece and the greater the heat generation that will occur, thus ultimately causing tool failure. On the other hand, positive skewness (sR_sk) indicates the presence of a small number of spikes on the flank surface of the cutting tool, which could quickly wear off during the machining process.     

A Two-Stage Approach for Network Monitoring

A goal of network tomography is to infer the status (e.g. delay) of congested links internal to a network, through end-to-end measurements at boundary nodes (end-hosts) via insertion of probe signals. Because (a) probing constitutes traffic overhead, and (b) in any typical scenario, the number of congested links is a small fraction of the total number in the network, a desirable design objective is to identify those (few) congested links using a minimum number of probes. In this paper, we make a contribution to solving this problem, by proposing a new two-stage approach for this problem. First, we develop a binary observation model linking end-to-end observations with individual link statuses and derive necessary and sufficient conditions for whether at least one link in the network is congested. Stage I of the proposed method shows that achieving 1-identifiability with a minimum number of probes is equivalent to the familiar minimum set covering problem that can be efficiently solved via a greedy heuristic. A sequential algorithm is described, leading to a significantly lowered computational complexity vis-a-vis a batch algorithm. Next, a binary splitting algorithm originally developed in group testing is used to identify the location of the congested links. The proposed scheme is evaluated by simulations in OPNET and experiments on the PlanetLab testbed to validate the advantages of our 2-stage approach vis-a-vis a conventional (batch) algorithm.     

Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.     

Outage Performance of Uplink (UL) NOMA Network

Wireless Personal Communications - This paper proposes and analyses the power allocation coefficient normalization for successive interference cancellation in power-domain non-orthogonal multiple...     

Reliable before-fabrication forecasting of MEMS piezoresistive pressure sensor: mathematical modelling and numerical simulation

Microsystem Technologies - Micro-mechanical systems (MEMS) based piezoresistive pressure sensors have significant importance in several pressure sensor devices in real world, i.e., aviation, IoT...     

A dynamic model for short-term prediction of stream attributes

Multiple data streams coming out of a complex system form the observable state of the system. The streams may correspond to various sensors attached with the system or outcome of internal processes. Such stream data may consist of multiple attributes and may differ in terms of their frequency of generation and observation. The streams may have dependency among themselves. One will have to rely on such data streams for monitoring the health of the system or to take any corrective measure. Predicting the value of certain stream data is an important task that can help one to take decision and act accordingly. In this work, a simple but generic visualization of a complex system is presented and thereafter a linear regression-based dynamic model for short-term prediction is proposed. The model is based on the past history of the attributes of multiple streams as suggested by the domain experts. But, it automatically determines the meaningful attributes and reformulates the model. The model is also re-computed if the prediction error exceeds the allowable tolerance. All these make the model dynamic. Experiment is carried out with stock market data streams to predict the close value well in advance. It is observed that in terms of quality of prediction and performance metric, the proposed model is quite effective.     

Morphology,Mineralogy and Mixing of Individual Atmospheric Particles Over Kanpur (IGP): Relevance of Homogeneous Equivalent Sphere Approximation in Radiative Models

Estimation of the direct radiative forcing (DRF) by atmospheric particles is uncertain to a large extent owing to uncertainties in their morphology (shape and size), mixing states, and chemical composition. A region-specific database of the aforementioned physico-chemical properties (at individual particle level) is necessary to improve numerically-estimated optical and radiative properties. Till date, there is no detailed observation of the above mentioned properties over Kanpur in the Indo-Gangetic Plain (IGP). To fill this gap, an experiment was carried out at Kanpur (IITK; 26.52°N, 80.23°E, 142 m msl), India from April to July, 2011. Particle types broadly classified as (a) Cu-rich particles mixed with carbon and sulphur (b) dust and clays mixed with carbonaceous species (c) Fe-rich particles mixed with carbon and sulfur and (d) calcite (CaCO₃) particles aged with nitrate, were observed. The frequency distributions of aspect ratio (AR; indicator of extent of particle non-sphericity) of total 708 particles from April to June reveal that particles with aspect ratio range >1.2 to ≤1.4 were abundant throughout the experiment except during June when it was found to shift to high AR range, >1.4 to ≤1.6 (followed with another peak of AR i.e. >2 to ≤2.4) due to dust storm conditions enhancing the occurrence of more non-spherical particles over the sampling site. The spherical particles (and close to spherical shape; AR range, 1.0 to ≤1.2) were found to be <20% throughout the experiment with a minimum (11.5%) during June. Consideration of Homogeneous Equivalent Sphere Approximation (HESA) in the optical/radiative model over the study region is found to be irrelevant during the campaign.