Energy-Efficient Food Processing: Principles and Practices

2014 ◽  
pp. 645-688
Keyword(s):  
Food Processing ◽  
Energy Efficient

scholarly journals Novel, energy efficient and green cloud point extraction: technology and applications in food processing

2019 ◽  
Vol 56 (2) ◽  
pp. 524-534 ◽  
Author(s):  
S. S. Arya ◽  
Admajith M. Kaimal ◽  
Moksha Chib ◽  
Sachin K. Sonawane ◽  
Pau Loke Show
Keyword(s):  
Cloud Point ◽  
Food Processing ◽  
Energy Efficient ◽  
Cloud Point Extraction ◽  
Extraction Technology ◽  
Green Cloud

Novel, Nonthermal, Energy Efficient, Industrially Scalable Hydrodynamic Cavitation – Applications in Food Processing

2019 ◽  
Vol 36 (7) ◽  
pp. 668-691 ◽  
Author(s):  
S. S. Arya ◽  
O. Sawant ◽  
Sachin K. Sonawane ◽  
P. L Show ◽  
A. Waghamare ◽  
...  
Keyword(s):  
Food Processing ◽  
Energy Efficient ◽  
Hydrodynamic Cavitation

Hospital Foodservice – 1978 and Beyond

1978 ◽  
Vol 41 (6) ◽  
pp. 471-475
Author(s):  
NAN UNKLESBAY
Keyword(s):  
Health Care ◽  
Food Processing ◽  
Energy Efficient ◽  
Energy Resources ◽  
Future Trends ◽  
Quality And Safety ◽  
Resource Usage ◽  
Research Activities ◽  
The Future ◽  
Effective Use

This paper (a) discusses how changes within the health care and food processing industries have influenced development of alternate foodservice systems and (b) projects some future trends related to resource usage. Schematic diagrams for four alternate foodservice systems are presented and discussed. The need for strengthening cooperation among food processing and foodservice industries is emphasized. Research activities related to the quality and safety of foods within each of these systems have been limited. In addition, these foodservice systems evolved without adequate consideration of effective use of energy resources. In the future, food processors and foodservice managers will have to coordinate their functions to serve good quality, energy-efficient menu items.

Performance Evaluation of AFOD Protocol for Energy Efficient Routing

2011 ◽  
Author(s):  
B. Smitha Shekar ◽  
M. Sudhakar Pillai ◽  
G. Narendra Kumar
Keyword(s):  
Performance Evaluation ◽  
Energy Efficient ◽  
Energy Efficient Routing

Distributed Entropy Energy-Efficient Clustering algorithm for cluster head selection (DEEEC)

2020 ◽  
Vol 39 (6) ◽  
pp. 8139-8147
Author(s):  
Ranganathan Arun ◽  
Rangaswamy Balamurugan
Keyword(s):  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Second Stage ◽  
Energy Efficient Clustering ◽  
Two Stages ◽  
Ch Selection

In Wireless Sensor Networks (WSN) the energy of Sensor nodes is not certainly sufficient. In order to optimize the endurance of WSN, it is essential to minimize the utilization of energy. Head of group or Cluster Head (CH) is an eminent method to develop the endurance of WSN that aggregates the WSN with higher energy. CH for intra-cluster and inter-cluster communication becomes dependent. For complete, in WSN, the Energy level of CH extends its life of cluster. While evolving cluster algorithms, the complicated job is to identify the energy utilization amount of heterogeneous WSNs. Based on Chaotic Firefly Algorithm CH (CFACH) selection, the formulated work is named “Novel Distributed Entropy Energy-Efficient Clustering Algorithm”, in short, DEEEC for HWSNs. The formulated DEEEC Algorithm, which is a CH, has two main stages. In the first stage, the identification of temporary CHs along with its entropy value is found using the correlative measure of residual and original energy. Along with this, in the clustering algorithm, the rotating epoch and its entropy value must be predicted automatically by its sensor nodes. In the second stage, if any member in the cluster having larger residual energy, shall modify the temporary CHs in the direction of the deciding set. The target of the nodes with large energy has the probability to be CHs which is determined by the above two stages meant for CH selection. The MATLAB is required to simulate the DEEEC Algorithm. The simulated results of the formulated DEEEC Algorithm produce good results with respect to the energy and increased lifetime when it is correlated with the current traditional clustering protocols being used in the Heterogeneous WSNs.

A Survey on Hierarchical Cluster Based Secure Routing Protocols and Key Management Schemes in Wireless Sensor Networks

2018 ◽  
pp. 18-26
Author(s):  
Yugashree Bhadane ◽  
Pooja Kadam
Keyword(s):  
Routing Protocol ◽  
Routing Protocols ◽  
Key Management ◽  
Energy Efficient ◽  
Base Station ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Management Schemes ◽  
Cluster Based Routing

Now days, wireless technology is one of the center of attention for users and researchers. Wireless network is a network having large number of sensor nodes and hence called as “Wireless Sensor Network (WSN)”. WSN monitors and senses the environment of targeted area. The sensor nodes in WSN transmit data to the base station depending on the application. These sensor nodes communicate with each other and routing is selected on the basis of routing protocols which are application specific. Based on network structure, routing protocols in WSN can be divided into two categories: flat routing, hierarchical or cluster based routing, location based routing. Out of these, hierarchical or cluster based routing is becoming an active branch of routing technology in WSN. To allow base station to receive unaltered or original data, routing protocol should be energy-efficient and secure. To fulfill this, Hierarchical or Cluster base routing protocol for WSN is the most energy-efficient among other routing protocols. Hence, in this paper, we present a survey on different hierarchical clustered routing techniques for WSN. We also present the key management schemes to provide security in WSN. Further we study and compare secure hierarchical routing protocols based on various criteria.

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