Thermally activated deformation in dilute zirconium/oxygen alloys

The effect of temperature and strain-rate on the yield and flow stress of zirconium, containing oxygen in the range of 0.09 to about 2.5 at. % has been examined at temperatures between 77 and 700° K. The above measurements were coupled with strain rate change tests and stress-relaxation experiments, so that all the deformation parameters associated with thermal activation could be evaluated.The results of these measurements showed that the thermal component of flow stress increases with increasing oxygen content of the alloy. Two stages of activation were found to occur for all these alloys. The first stage was associated with the unpinning of dislocation loops from impurity pinning points. At higher temperatures, because of the unpinning of many impurity pinning points, a second stage of activation associated with a different mechanism was found to occur. The variation of certain parameters associated with this stage of deformation strongly suggests the Peierls-Nabarro force as the controlling criterion.     

Multiattribute Bayesian Acceptance Sampling Plans for Screening and Scrapping Rejected Lots

A general model for multiattribute Bayesian acceptance sampling plans is developed which incorporates the multiattribute utility function of a decision maker in its design. The model accommodates various dispositions of rejected lots such as screening and scrapping. The disposition of rejected lots is shown to have a substantial impact on the solution approach used and on the ease of incorporation of multiattribute utility functions in terms of their measurement complexity, functional form, and parameter estimation. For example, if all attributes are screenable upon rejection, and the prior distributions of lot quality on each attribute are independent, then an optimal multiattribute sampling plan can be obtained simply by solving for an optimal single sampling plan on each attribute independently. A discrete search algorithm, based on pattern search, is also developed and shown to be very effective in obtaining an optimal multiattribute inspection plan when such separability cannot be accomplished.     

Electroreduction of phenyl cyanide and benzyl cyanide on nickel cathode

An electrochemical method for preparation of primary amines from organic cyanides using nickel black deposited over graphite substrate as cathode has been studied. It has been observed that it is possible to reduce benzyl cyanide both in ethanolic sulphuric acid and in aqueous ethanolic ammonium sulphate media. But with phenyl cyanide, the reduction is efficient only in ethanolic sulphuric acid medium. Both in laboratory and 75 A scale experiments 62–66% yield has been obtained at a current efficiency of 36–44% for benzylamine. Similarly a yield ranging from 60–80% with a current efficiency of 36–52% has been obtained for β-phenylethylamine both in laboratory scale and also in large scale experiments. Results of operation of a 500 A cell for the preparation of β-phenylethylamine are also presented.     

A rationale for transformation twins in ordered alloys

A mechanism based on the growth of the ordered phase in the disordered matrix is advanced to explain the presence of numerous transformation twins in the ordered structure. The merits of this mechanism are considered on the basis of available experimental results on ordered alloys.     

PCSSHO: An implementation of Percentage of Circle Search and Spotted Hyena Optimizer for multi-constraint load balancing and routing framework in FANET

Flying ad hoc network (FANET) is a technology that has seen tremendous growth in the past years due to its application in various military and civil developments. Conventional topology-aided routing schemes are not suitable for large-scale FANETs. This is because of the higher mobility rate in UAVs with the architecture differences. Hence, several path entries in routing become invalid and the neighboring nodes can be occupied before the interruption. Hence, it is very important to solve the afore-explained issues in FANET. Initially, the task is assigned to the UAVs. These tasks are performed by satisfying the demands such as timing, congestion, and energy to attain the effective load-balancing performance. Then, the optimal clustering and cluster head (CH) selection are performed using the developed Percentage of Circle Search and Spotted Hyena Optimizer (PCSSHO) in the communication path. Here, the feature selection is done based on constraints like position, speed, moving direction, height variation, link quality, and inter- and intra-cluster distance. Then, the developed PCSSHO model performs routing by considering different constraints such as “end-to-end delay, delivery ratio, power consumption, and link quality.” Thus, the recommenced load balancing model in FANET secures an enhanced performance rate than the conventional load balancing frameworks.     

Market Clearing and Settlement Using Participant Based Distributed Slack Optimal Power Flow Model for a Double Sided Electricity Auction Market –Part I

AC and DC OPF models are widely used in the industry for market clearing and settlement of primary electricity market. Research works available in literature have used locational marginal price to price electricity. But this research work by using Participant Based Distributed Slack Power Flow and a unique delivery/withdrawal point for energy called “Market Center” provides a new framework for pricing the electricity. Using the Participant Based Distributed Slack Power Flow Model a Participant based Distributed Slack Non Linear Optimal Power Flow model for market clearing and settlement of primary transaction in a double sided electricity auction market is proposed in Part 1 of this paper. Part II of this paper proposes an equivalent lumped linear model for faster convergence. The optimal solution gives the optimal schedules of the individual participants. The formulae to decompose the amount payable to GENCO participant and marginal price to be received from the DISCO participant into its components are also derived which is different from all available techniques in literature which calculate bus wise nodal prices. The proposed model is tested on Radial Five bus system and PJM system for market clearing and settlement of primary electricity market.     

How do journals on the periphery compare with mainstream scientific journals?

Based on the premise that citations in scientific journals can tell us a lot about the journals, we have compared Indian journals in the fields of astronomy, physics, chemistry, biochemistry, geology and ecology with leading world journals. The two criteria compared are the age of references and the journals often cited in each of the journals considered. Our results show that although overall Indian science is mediocre, parts of India's scientific enterprise are cognitively better related to world science. The peripherality is not uniform across the board, but some areas like astronomy and to some extent physics are closer to the central or mainstream science than others. Although citation analysis is not normally used for cross-field comparisons, this paper demonstrates that, if used judiciously, citation analysis can yield valuable insights into issues involving many fields.     

Market Clearing and Settlement Using Participant Based Distributed Slack Optimal Power Flow Model for a Double Sided Electricity Auction Market – Part II

Even though non-linear Optimal Power Flow model proposed in part I of this paper provide accurate results there are difficulties in solving a full non-linear Optimal Power Flow model since it is a very time consuming. Due to speed and robustness, Linear Programming model is preferred by the system operators for nodal price calculations. It is a challenge to incorporate transmission losses into the losses linear DC power model. In this paper to model line flow operating limit inequality constraint a lossless Participant Based Distributed Slack DC Power Flow model is derived from Newton-Raphson state correction scheme used in part I of this work. An equivalent lumped linear model for the Participant Based Distributed Slack Lumped Nonlinear Optimal Power Flow model called Participant Based Distributed Slack Lumped Linear Optimal Power Flow model is developed in part II of this paper. The results for market clearing and settlement of double sided electricity market by the proposed lumped linear model are compared with the nonlinear model proposed in part I of this work using case studies on PJM system, IEEE 30 bus system and IEEE 118 bus system. The results obtained indicate the speed and robustness of the proposed linear model.     

Simulation and measurement of supply and substrate noise in mixed-signal ICs

Digital noise in mixed-signal circuits is characterized using a scalable macromodel for substrate noise coupling. The noise coupling obtained through simulations is verified with measured data from a digital noise generator and noise sensitive analog circuits fabricated in the 0.35-/spl mu/m heavily doped CMOS process. The simulations and measurements also demonstrate the effectiveness of including grounded guard rings and separating bulk and supply pins in digital circuits to reduce substrate coupling.     

Hybrid Fuzzy Adaptive Wiener Filtering with Optimization for Intrusion Detection

Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.