scholarly journals Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
M. S. Leite ◽  
T. L. Fujiki ◽  
F. V. Silva ◽  
A. M. F. Fileti
Keyword(s):  
Network Architecture ◽  
Design Methodology ◽  
Protein Denaturation ◽  
Plant Design ◽  
Inference System ◽  
Enzyme Recovery ◽  
And Performance ◽  
Neural Predictive Control ◽  
Rule Bases ◽  
Intelligent Controllers

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity.

Creating a growth mindset

2017 ◽  
Vol 16 (4) ◽  
pp. 155-160
Author(s):  
Ian Johnston
Keyword(s):  
Case Studies ◽  
Design Methodology ◽  
Growth Mindset ◽  
Cultural Space ◽  
Content Type ◽  
Fixed Mindset ◽  
And Performance

Purpose This paper aims to show that everything a business does is fundamentally reliant on its culture. Culture determines how successful a strategy is and whether that strategy can be executed. If the culture in a business is out of alignment, it is imperative to change it. This paper examines how HR professionals can take ownership of this cultural space and help to create a growth mindset throughout the organisation. Design/methodology/approach The paper is based on experience gained through working with several large organisations to transform their people culture and performance by embracing a growth mindset and to help their HR leadership become the early champions of change, thus ensuring the process was successfully delivered. The paper includes case studies of two organisations where successful cultural shaping delivered improved results. Findings Companies with a growth mindset will outperform those with a fixed mindset. Changing mindsets is not overly complex, but it requires flawless implementation with the HR leaders at the forefront. Originality/value As Lou Gerstner, who turned around the computing giant IBM, said “I finally realised that culture is not part of the game, it is the game”. By understanding how individual mindsets impact culture, HR professionals can own and drive their organisation’s culture-shaping efforts.

Phosphate removal in real anaerobic supernatants: modelling and performance of a fluidized bed reactor

1998 ◽  
Vol 38 (1) ◽  
pp. 275-283 ◽  
Author(s):  
P. Battistoni ◽  
P. Pavan ◽  
F. Cecchi ◽  
J. Mata-Alvarez
Keyword(s):  
Fluidized Bed ◽  
Contact Time ◽  
Fluidized Bed Reactor ◽  
Phosphate Removal ◽  
Plant Design ◽  
Air Stripping ◽  
And Performance ◽  
Ph Range ◽  
Very High ◽  
A2o Process

Phosphate removal in anaerobic supernatant coming from a centrifugation sludge station of an A2O process is studied. A fluidized bed reactor is employed to crystallize phosphate as hydroxyapatite or struvite using only air stripping to reach the supersaturation pH. The classic composition of supernatant (alkalinity 3550 mgCaCO3/l, PO4 139 mg/l, Mg 24 mg/l) does not require any addition of chemicals for phosphate removal. Seventeen runs are performed in a bench scale FBR obtaining very high conversion and removal efficiency and phosphate loss in the effluent ≤3.5%. The use of Ca or Mg enriched supernatant has no meaningful influence on efficiency, but it determines the prevalent salt formed between MAP or HAP. Efficiency can be related to pH and sand contact time in a double saturational model. The half efficiency constants: 0.075 h for t and 7.75 pH, have an important role in the process knowledge and optimization of plant design. Exhaust sand analysis indicates the same composition at the top, bottom and mean of the sand bed (39% mol MAP and 61% mol HAP). This result together with the high half efficiency constant for contact time indicate that the phosphate growth on the bed is not competitive. Finally, the phosphate release from the plant is studied. Results show a weak release rate, equivalent to 2.8-10% d−1 phosphate as MAP, obtained at an operative pH range of 8.1-8.4.

An artificial neural network approach to discrete-event simulation

1995 ◽  
Vol 9 (1) ◽  
pp. 37-49 ◽  
Author(s):  
Ian Flood ◽  
Kenneth Worley
Keyword(s):  
Neural Network ◽  
Discrete Event Simulation ◽  
Network Architecture ◽  
Discrete Event ◽  
Network Approach ◽  
Neural Network Approach ◽  
Event Simulation ◽  
The Neural Network ◽  
Component Processes ◽  
And Performance

AbstractThis paper proposes and evaluates a neural network-based method for simulating manufacturing processes that exhibit both noncontinuous and stochastic behavior processes more conventionally modeled, using discrete-event simulation algorithms. The incentive for developing the technique is its potential for rapid execution of a simulation through parallel processing, and facilitation of the development and improvement of models particularly where there is limited theory describing the dependence between component processes. A brief introduction is provided to a radial-Gaussian neural network architecture and training process, the system adopted for the work presented in this paper. A description of the basic approach proposed for applying this technology to simulation is then described. This involves the use of a modularized neural network approach to model construction and the prediction of the occurrence of events using information retained from several previous states of the simulation. A class of earth-moving systems, comprising a push-dozer and a fleet of scrapers, is used as the basis for assessing the viability and performance of the proposed approach. A series of experiments show the neural network to be capable of both capturing the characteristic behavior and making an accurate prediction of production rates of scraper-based earth-moving systems. The paper concludes with an indication of some areas for further development and evaluation of the technique.

scholarly journals Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Aref M. al-Swaidani ◽  
Waed T. Khwies
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Network Architecture ◽  
Supplementary Cementitious Material ◽  
Natural Pozzolans ◽  
Long Time ◽  
Ann Models ◽  
Artificial Neural ◽  
And Performance ◽  
And Training

Numerous volcanic scoria (VS) cones are found in many places worldwide. Many of them have not yet been investigated, although few of which have been used as a supplementary cementitious material (SCM) for a long time. The use of natural pozzolans as cement replacement could be considered as a common practice in the construction industry due to the related economic, ecologic, and performance benefits. In the current paper, the effect of VS on the properties of concrete was investigated. Twenty-one concrete mixes with three w/b ratios (0.5, 0.6, and 0.7) and seven replacement levels of VS (0%, 10%, 15%, 20%, 25%, 30%, and 35%) were produced. The investigated concrete properties were the compressive strength, the water permeability, and the concrete porosity. Artificial neural networks (ANNs) were used for prediction of the investigated properties. Feed-forward backpropagation neural networks have been used. The ANN models have been established by incorporation of the laboratory experimental data and by properly choosing the network architecture and training processes. This study shows that the use of ANN models provided a more accurate tool to capture the effects of five parameters (cement content, volcanic scoria content, water content, superplasticizer content, and curing time) on the investigated properties. This prediction makes it possible to design VS-based concretes for a desired strength, water impermeability, and porosity at any given age and replacement level. Some correlations between the investigated properties were derived from the analysed data. Furthermore, the sensitivity analysis showed that all studied parameters have a strong effect on the investigated properties. The modification of the microstructure of VS-based cement paste has been observed, as well.

They teach, but do they apply?

2019 ◽  
Vol 10 (3) ◽  
pp. 743-766
Author(s):  
Anete Petrusch ◽  
Guilherme Luís Roehe Vaccaro ◽  
Juliane Luchese
Keyword(s):  
Design Methodology ◽  
Additional Data ◽  
Effective Sample Size ◽  
Exploratory Research ◽  
Lean Thinking ◽  
Content Type ◽  
Administrative Services ◽  
The Usa ◽  
And Performance ◽  
The Uk

Purpose Although discussed for more than 20 years, information about Lean adoption in higher education institutions (HEIs) is scarce, especially in developing countries. This research aims to investigate the degree of Lean thinking adoption on administrative services of Brazilian private HEIs. The results are compared to studies from USA and UK, highlighting the maturity on enablers, principles, tools and performance measures related to Lean. Design/methodology/approach A quantitative survey research was carried out. The instrument is adapted for HEIs from the proposal of Malmbrandt and Åhlström (2013) for Lean services. Cronbach’s alpha and factor analysis were used to validate the adapted instrument. Additional data analysis was based on non-parametric tests. Findings No evidence of broad implementation of Lean thinking in administrative processes of Brazilian private HEIs was found, with the adoption being incipient. The results are convergent to those presented by other studies in the USA and the UK. There is a gap between the existing knowledge about Lean in the academic sphere of the HEIs and its application on their academic processes. Research limitations/implications The effective sample size was of 47, despite contacts being sent to 2,090 institutions. This sample allows exploratory research, although further research is required. Results are adherent to those found in research from other countries. Originality/value The research presents descriptive and exploratory results regarding the adoption of Lean in Brazilian HEIs. No previous similar research was found in the literature.

scholarly journals The Science DMZ: A Network Design Pattern for Data-Intensive Science

2014 ◽  
Vol 22 (2) ◽  
pp. 173-185 ◽  
Author(s):  
Eli Dart ◽  
Lauren Rotman ◽  
Brian Tierney ◽  
Mary Hester ◽  
Jason Zurawski
Keyword(s):  
Network Design ◽  
Network Architecture ◽  
Design Patterns ◽  
Data Transfer ◽  
Scientific Discovery ◽  
High Capacity ◽  
Scientific Progress ◽  
Scientific Data ◽  
Data Intensive ◽  
And Performance

The ever-increasing scale of scientific data has become a significant challenge for researchers that rely on networks to interact with remote computing systems and transfer results to collaborators worldwide. Despite the availability of high-capacity connections, scientists struggle with inadequate cyberinfrastructure that cripples data transfer performance, and impedes scientific progress. The ScienceDMZparadigm comprises a proven set of network design patterns that collectively address these problems for scientists. We explain the Science DMZ model, including network architecture, system configuration, cybersecurity, and performance tools, that creates an optimized network environment for science. We describe use cases from universities, supercomputing centers and research laboratories, highlighting the effectiveness of the Science DMZ model in diverse operational settings. In all, the Science DMZ model is a solid platform that supports any science workflow, and flexibly accommodates emerging network technologies. As a result, the Science DMZ vastly improves collaboration, accelerating scientific discovery.

scholarly journals Sixth Generation (6G) Cognitive Radio Network (CRN) Application, Requirements, Security Issues, and Key Challenges

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Muhammad Muzamil Aslam ◽  
Liping Du ◽  
Xiaoyan Zhang ◽  
Yueyun Chen ◽  
Zahoor Ahmed ◽  
...  
Keyword(s):  
Communication Networks ◽  
Channel Coding ◽  
Network Architecture ◽  
Satellite Communication ◽  
Performance Metrics ◽  
Spectral Energy ◽  
Future Technology ◽  
Security Issues ◽  
Sixth Generation ◽  
And Performance

Recently, 5G installation has been started globally. Different capabilities are in the consistent procedure, like ultrareliability, mass connectivity, and specific low latency. Though, 5G is insufficient to meet all the necessities of the future technology in 2030 and so on. Next generation information and communication technology is playing an important role in attraction of researchers, industries, and technical people. With respect to 5G networks, sixth-generation (6G) CR networks are anticipated to familiarize innovative use cases and performance metrics, such as to offer worldwide coverage, cost efficiency, enhanced spectral, energy improved intelligence, and safety. To reach such requirements, upcoming 6G CRNs will trust novel empowering technologies. Innovative network architecture and transmission technologies and air interface are of excessive position, like multiple accesses, waveform design, multiantenna technologies, and channel coding schemes. (1) To content, the condition should be of worldwide coverage, there will be no limit on 6G to global CR communication networks that may require to be completed with broadcast networks, like satellite communication networks, therefore, attaining a sea integrated communication network. (2) The spectrums overall will be entirely travelled to the supplementary rise connection density data rates in optical frequency bands, millimeter wave (mmWave), sub-6 GHz, and terahertz (THz). (3) To see big datasets created because of tremendously varied CR communication networks, antenna rush, diverse communication scenarios, new provision necessities, wide bandwidth, and 6G CRNs will allow an innovative variety of intelligent applications with the assistance of big data and AI technologies. (4) Need to improve network security when deploying 6G technology in CR networks. 6G is decentralized, intended, intelligent innovative, and distributed network. In this article, we studied a survey of current developments and upcoming trends. We studied the predicted applications, possible technologies, and security issues for 6G CR network communication. We also discussed predicted future key challenges in 6G.

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