Hybrid stiff-string–polynomial basis functions for vibration analysis of high speed rotating beams

A new finite element is developed for free vibration analysis of high speed rotating beams using basis functions which use a linear combination of the solution of the governing static differential equation of a stiff-string and a cubic polynomial. These new shape functions depend on rotation speed and element position along the beam and account for the centrifugal stiffening effect. The natural frequencies predicted by the proposed element are compared with an element with stiff-string, cubic polynomial and quintic polynomial shape functions. It is found that the new element exhibits superior convergence compared to the other basis functions.     

Simultaneous dissolved oxygen and glucose regulation in fed-batch methionine production using decoupled input–output linearizing control

Methionine is one of the essential amino acids produced by fed-batch fermentation. The synthesis of methionine at the cellular level is strictly regulated and its process dynamics shows a nonlinear interaction between dissolved oxygen and glucose concentration. For controlling this process, a decoupled input–output linearizing controller (DIOLC) is derived. The model used for this purpose contains an exponential kinetic structure for describing the nonlinearities and metabolic switching function for describing oxygen dependency. The control system is square having two inputs and two outputs. The zero dynamics stability for internal variables and error convergence is proved. The performance of DIOLC is examined under high and low oxygen demand conditions. Four case studies are used to demonstrate that the DIOLC action is decoupled. The DIOLC also exhibited robust performance even for random variations up to ±20% in some parameters. In simulated experiments, using DIOLC produces 16 g l^?1 of methionine. The performance of PI controllers under identical conditions is given for comparison.     

State of the art content based image retrieval techniques using deep learning: a survey

In the recent years the rapid growth of multimedia content makes the image retrieval a challenging research task. Content Based Image Retrieval (CBIR) is a technique which uses features of image to search user required image from large image dataset according to the user’s request in the form of query image. Effective feature representation and similarity measures are very crucial to the retrieval performance of CBIR. The key challenge has been attributed to the well known semantic gap issue. The machine learning has been actively investigated as possible solution to bridge the semantic gap. The recent success of deep learning inspires as a hope for bridging the semantic gap in CBIR. In this paper, we investigate deep learning approach used for CBIR tasks under varied settings from our empirical studies; we find some encouraging conclusions and insights for future research.

     

Data base design for computer-integrated structural engineering

The most likely architecture for an integrated engineering software system is a series of application programs operating off a shared central data base. The data base is the most critical part of the system. This article proposes a design for such a data base. The steps involved in data base, design are first reviewed, and several requirements for an effective structural engineering data base system are identified. A data base design based on a component-connection abstraction model and the object-oriented data model is then presented.     

Application of genetic algorithm for unknown parameter estimations in cylindrical fin

This article deals with the application of the genetic algorithm (GA) for optimizing an inverse problem and retrieving unknown parameters in cylindrical fin geometry. Parameters such as the thermal conductivity and the heat transfer coefficient are attempted for estimation in order to satisfy a desired temperature field in the medium. The study is done for single-parameter and simultaneous two-parameter retrievals. The temperature field is calculated from a forward problem using the finite difference method using some known values of the properties. These properties are ultimately retrieved by an inverse approach using the GA. The study is done for different controlling parameters such as the number of generations, measurement errors and number of measurement locations. For two parameter simultaneous estimation, many combination of unknown parameters are observed to satisfy a given temperature field, and their ratio is only found to be successfully estimated. The present work is proposed to be useful for selecting the thermal properties which are required to satisfy a given temperature field.     

Modelling of navigation based LNA parameters using neural network technique

An approach to model the parameters of LNA which is ideal for GLONASS navigation system. To design LNA, multilayer perceptron architecture is used. The parameters of LNA are calculated using Levenberg Marquardt Backpropagation Algorithm for the frequency range 300 MHz to 18 GHz. ANN model is trained using Agilent MGA 71543 Low Noise Amplifier datasheet and this model shows high regression. The smith and polar charts are plotted for frequency range 300 MHz to 18 GHz and parameters are calculated for center frequency of L1 band of GLONASS, which is 1.602 GHz.     

Compact design of an MTJ-based non-volatile CAM cell with read/write operations

Microsystem Technologies - This paper presents a novel design of a magnetic tunnel junction (MTJ) based content addressable memory (CAM) cell with low power dissipation and small-time delay....     

Cooperative Target-centric Formation Control without Relative Velocity Measurements under Heterogeneous Networks

This paper proposes distributed control laws for a group of unmanned aerial vehicles (UAVs) to make and maintain a circular formation around a maneuvering target. The work considers usage of heterogeneous communication networks to achieve the desired formation. Two different scenarios are considered on velocity information. In both scenarios, it is assumed that each UAV has its own position and velocity measurements available to itself. However, the team is unable to exchange velocity information among themselves. In the first scenario, each agent uses its own position and velocity information in the consensus algorithm. In the second scenario, agents need only position information for the consensus algorithm. For both the approaches, each agent calculates a virtual estimate of target’s velocity from the received information and exchanges the estimate with its neighbors. The control algorithms are developed using heterogeneous communication networks to satisfy a communication bandwidth constraint. Three different communication networks are used to circulate position information, virtual estimates, and its time derivatives. The graphs representing communication networks are undirected and connected. Further, it is considered that there is at least one UAV (agent) receiving position, velocity, and acceleration information of the target. The agent receiving target’s position need not be the same agent which receives velocity and/or acceleration information of the maneuvering target. However, the target does not receive any information from any agent. Using Barbalat’s lemma, the stability of the target-centric formation of a group of UAVs is analyzed. The performance of the proposed laws are illustrated through numerical simulations.     

Isolating bugs in multithreaded programs using execution suppression

Memory‐related program failures in multithreaded programs can be caused by a variety of bugs. Concurrency bugs can occur due to unexpected or incorrect thread interleavings during execution. Other kinds of memory bugs, such as buffer overflows and uninitialized reads, may also occur in multithreaded as well as single‐threaded programs. Most prior techniques for isolating these bugs are specialized, addressing only one type of concurrency bug or certain types of other memory bugs. The memory corruption caused by these bugs can also undergo significant propagation during program execution. When a program failure finally occurs due to memory corruption, the true root cause of the failure may be effectively concealed as significant portions of memory may have become corrupted. We propose a general framework that can isolate the root cause of any failure in a multithreaded program that involves memory corruption and reveals at least a subset of this memory corruption. This includes three important types of concurrency bugs—data races, atomicity violations, and order violations—as well as other kinds of memory bugs. To account for propagation of memory corruption, our approach uses a dynamic technique called ‘execution suppression’ that iteratively reveals memory corruption in a failing execution to isolate the true root cause of the failure. Copyright © 2011 John Wiley & Sons, Ltd.