Producibility Analysis Using Metrics Based on Physical Process Models

This paper presents an approach to evaluating producibility which is intended to enhance the ability of engineers to quickly design low-cost and high-quality parts. We divide all production processes into two categories: trajectory-dominated processes in which a generic tool is moved in a trajectory to form the part shape, and process-physics-dominated processes in which shaped tools are used to form similarly shaped parts. We focus on process-physics-dominated processes and on producibility problems that arise because of part shape. We argue that for these processes the currently popular approach of representing parts as collections of geometric features may be inappropriate for evaluating producibility. We propose an alternative approach and representation. Our approach consists of first identifying the different failure modes of the process and then defining producibility metrics corresponding to the likelihood of encountering each failure mode. This set of metrics is used to represent the degree to which a part is easily manufactured. Finally, we demonstrate this approach by developing a set of metrics for evaluating the producibility of aluminum extrusions. We use extrusions from the Boeing 777 to validate the metrics.     

Effect of impurities on the corrosion behaviour of neodymium

The corrosion behaviour of neodymium contaminated with up to 0.9% C, up to 15% Fe and about 16% of Tb or Dy was examined in various aggressive environments. It was found that in acid media the C and Fe additions accelerated the corrosion process of the alloys. The Nd-base alloys were fairly resistant to corrosion in atmospheric conditions, however, the impurities worsened the corrosion behaviour in this environment as compared with pure Nd.     

The development of a program generator for programmable logic controllers

Programmable logic controllers (PLC) are very widely used for sequential logic control in manufacturing environments. PLCs serve to integrate materials handling and processes in automated manufacturing systems. Due to changing demands on manufacturing systems, frequently new control software needs to written and changes need to be made to existing control software. The productivity of such software development efforts can benefit from a software generation tool. We present an approach for the development of such a tool.     

Ultrasonic study on binary liquid mixtures of propiophenone with anilines and alkyl substituted anilines at T=303.15 to 318.15 K

Densities ‘ρ’, ultrasonic speeds of sound ‘u’ of binary mixtures of propiophenone (PPH) with aniline, N-Methylaniline, N,N-dimethylaniline and N,N-diethylaniline were measured over the entire composition range from 303.15 K to 318.15 K and at atmospheric pressure 0.1 MPa. Experimental data of ultrasonic sound were compared and discussed with the computed values of ‘u’ from various velocity theories like Nomoto’s relation (U_NOM), impedance relation (U_IMP), Van Dael and Vangeel’s ideal mix relation (U_VDV), Rao’s specific velocity relation (U_RAO), Junjie’s theory (U_JUN) and Jouyban-Acree’s (U_JOE) relation for the above binary mixtures over the entire mole fraction range at the studied temperatures. The results are satisfactory and are in agreement between the theoretical and the experimental values. Further, the molecular interaction parameter (α), average percentage error and Chi-square test values were computed by using the values of experimental and theoretical ultrasonic velocities. The Δu values were correlated with Redlich-Kister polynomial equation to compute the coefficients and the standard deviations of the binary mixtures. The results were analyzed in terms of intermolecular interactions.     

Blockchain Assisted Disease Identification of COVID-19 Patients with the Help of IDA-DNN Classifier

Wireless Personal Communications - Globally, millions of people were affected by the Corona-virus disease-2019 (COVID-19) causing loads of deaths. Most COVID-19 affected people recover in a few...     

Distributed classification for image spam detection

Spam appears in various forms and the current trend in spamming is moving towards multimedia spam objects. Image spam is a new type of spam attacks which attempts to bypass the spam filters that mostly text-based. Spamming attacks the users in many ways and these are usually countered by having a server to filter the spammers. This paper provides a fully-distributed pattern recognition system within P2P networks using the distributed associative memory tree (DASMET) algorithm to detect spam which is cost-efficient and not prone to a single point of failure, unlike the server-based systems. This algorithm is scalable for large and frequently updated data sets, and specifically designed for data sets that consist of similar occurring patterns.We have evaluated our system against centralised state-of-the-art algorithms (NN, k-NN, naive Bayes, BPNN and RBFN) and distributed P2P-based algorithms (Ivote-DPV, ensemble k-NN, ensemble naive Bayes, and P2P-GN). The experimental results show that our method is highly accurate with a 98 to 99% accuracy rate, and incurs a small number of messages—in the best-case, it requires only two messages per recall test. In summary, our experimental results show that the DAS-MET performs best with a relatively small amount of resources for the spam detection compared to other distributed methods.     

Employee dispositions to job and organization as antecedents and consequences of information systems use

Organizations implement information systems to improve employee productivity and engender favourable organizational outcomes. Although there is evidence of positive outcomes of system use, research has suggested that system use may lead to negative consequences for employees and organizations. There has been limited research that focuses on how employees' use of information systems in the workplace is associated with their positive and negative dispositions to job and organization. We develop and test a model that posits that dispositions to job (ie, job satisfaction, job security, job anxiety, and emotional exhaustion), and organization (ie, organizational commitment and organizational trust) will play a dual role of antecedents and consequences of system use. We conducted 2 longitudinal studies in the context of 2 different systems—a functional system and an enterprise system—and found support for our hypotheses (N = 257 and 181, respectively). We found that preimplementation job and organizational dispositions significantly predicted both lean and rich measures of system use. Further, we found that rich measures of system use (ie, cognitive absorption use and deep structure use) had differential impacts on postimplementation employee dispositions—functional system use had a positive impact and enterprise system use had a negative impact. Overall, our findings offer a comprehensive understanding of system use, and its antecedents and consequences for employees in organizations.     

Cuckoo search based resource optimization of datacenters

With advancements in virtualization technology, datacenters are often faced with the challenge of managing large numbers of virtual machine (VM) requests. Due to this large amount of VM requests, it has become practically impossible to search all possible VM placements in order to find a solution that best optimizes certain design objectives. As a result, managers of datacenters have resorted to the employment of heuristic optimization algorithms for VM placement. In this paper, we employ the cuckoo search optimization (CSO) algorithm to solve the VM placement problem of datacenters. Firstly, we use the CSO to optimize the datacenter for the minimization of the number of physical machines used for placement. Secondly, we implement a multiobjective CSO algorithm to simultaneously optimize the power consumption and resource wastage of the datacenter. Simulation results show that both CSO algorithms outperform the reordered grouping genetic algorithm (RGGA), the grouping genetic algorithm (GGA), improved least-loaded (ILL) and improved FFD (IFFD) methods of VM placement.     

RETRACTED ARTICLE: Design of Three Stage Cascaded Low Power CMOS Operational Trans Conductance Amplifier (OTA) for ECG Applications

Multimedia Tools and Applications - The primary test incorporates intensifying the weak signal within the noisy environment. The OTA configuration is all around used to evacuate...     

Capacity in fading environment based on soft sensing information under spectrum sharing constraints

In this paper, the ergodic channel capacity for a secondary user is investigated using soft sensing information about primary user activity in a shared channel under joint peak transmit power and average received interference power constraints for Nakagami-m fading channel. The results of the proposed power adaptation scheme illustrate the effect of communication environment parameters and soft sensing information about primary user activity on the channel capacity of secondary user. In particular, the effect of cross link channel state information to maximize the channel capacity for the power adaptation scheme is emphasized by considering the Lagrangian optimization problem for joint peak transmit power and average interference power constraints. Moreover, the performance of the primary user is also investigated considering the interference of the secondary user to the primary in spectrum sharing environment in terms of transmission rate and average channel capacity.