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Kesavan, R.
- Efficient Energy Consumption Mechanism for Wireless Networks
Abstract Views :155 |
PDF Views:2
Authors
R. Kesavan
1,
V. Thulasi Bai
2
Affiliations
1 Department of Computer Applications, Jaya Engineering College, Chennai, IN
2 Electronics and Communication Engineering Department, Prathyusha Institute of Technology and Management, Chennai, IN
1 Department of Computer Applications, Jaya Engineering College, Chennai, IN
2 Electronics and Communication Engineering Department, Prathyusha Institute of Technology and Management, Chennai, IN
Source
Networking and Communication Engineering, Vol 5, No 6 (2013), Pagination: 300-304Abstract
In cooperative networks, transmitting and receiving nodes recruit neighboring nodes to assist in communication. We model a cooperative transmission link in wireless networks as a transmitter cluster and a receiver cluster. We then propose a cooperative communication protocol for establishment of these clusters and for cooperative transmission of data. We derive the upper bound of the capacity of the protocol, and we analyze the end-to-end robustness of the protocol to data-packet loss, along with the tradeoff between energy consumption and error rate. The analysis results are used to compare the energy savings and the end-to-end robustness of our protocol with two non-cooperative schemes, as well as to another cooperative protocol published in the technical literature. The comparison results show that, when nodes are positioned on a grid, there is a reduction in the probability of packet delivery failure by two orders of magnitude for the values of parameters considered. Up to 80% in energy savings can be achieved for a grid topology, while for random node placement our cooperative protocol can save up to 40% in energy consumption relative to the other protocols. The reduction in error rate and the energy savings translate into increased lifetime of cooperative sensor networks.Keywords
Clustering, Cooperative Transmission, EWMA, Can, Sensor Networks.- Optimization of Amylase Production from Bacillus subtilis and Pseudomonas aeruginosa Using Sugarcane Bagasses by Submerged Fermentation
Abstract Views :140 |
PDF Views:1
Authors
Affiliations
1 PG and Research Department of Biochemistry, Enathi Rajappaa College, Enathi, Pattukkottai, Thanjavur Dt., Tamilnadu, IN
2 34 Chellapillaiyar Kovil Street, Karanthai, Thanjavur -613002, IN
1 PG and Research Department of Biochemistry, Enathi Rajappaa College, Enathi, Pattukkottai, Thanjavur Dt., Tamilnadu, IN
2 34 Chellapillaiyar Kovil Street, Karanthai, Thanjavur -613002, IN
Source
Research Journal of Science and Technology, Vol 4, No 2 (2012), Pagination: 86-89Abstract
Enzymes are considered as nature’s catalysis most enzymes today (and in future) produced from the microorganisms. In the present study, Bacillus subtilis and Pseudomonas aeruginosa were isolated from the soil samples. The isolated organisms were identified using standard microbiological methods. The inoculums were prepared with waste substrate (sugarcane bagasse). The isolated bacterial strain were inoculated in the medium and incubated at 30°C for 3 days. The high-level amylase production was observed in Bacillus subtilis inoculated medium so this strain used for the optimization studies. The amylase activity was optimized in various physical parameters such as temperature, pH and chemical parameters like nitrogen and carbon sources. The maximum production of amylase was recorded at 35° C and pH 7.0. The amylase production by Bacillus subtilis was recorded maximum in starch-supplemented medium when compared to other carbon sources (maltose and glucose). Among the various nitrogen sources (Ammonium sulphate, ammonium chloride and ammonium nitrate) used, Ammonium sulphate supplemented medium showed the significant results in the production of amylase by Bacillus subtilis.Keywords
Amylase, Sugarcane Bagasse, Bacillus Subtilis, Pseudomonas aeruginosa and Submerged Fermentation.- Lean Manufacturing for Cycle Time Reduction in an Assembly Shop
Abstract Views :149 |
PDF Views:0
Authors
Affiliations
1 Dept. of Production Technology, M.I.T. Campus, Anna University, Chrompet, Chennai, IN
1 Dept. of Production Technology, M.I.T. Campus, Anna University, Chrompet, Chennai, IN
Source
Manufacturing Technology Today, Vol 9, No 6 (2010), Pagination: 11-17Abstract
In order to sustain in present competitive market, on-time delivery, excellent quality and aesthetic are very much essential. The objective of this paper is reducing the cycle time of assembly of automobile door trim panels by implementing various modernized techniques using lean manufacturing concepts. It is evident from the past reports that in the existing system the cycle time is more and it has poor aesthetic. Here a leading automobile company's front door panel assembly is considered and the assembly line is modernized and automated to reduce the cycle time and to improve the aesthetic. The outcome of this paper leads to substantial reduction in cycle time, reduced cost of maintenance, reduced defects, better utilization of machines and man power. Statistical quality control is carried out on the new method of welding joints. The result shows that the process is under control. Also, the proposed system is validated for its increased productivity and for return on investment (ROI). It has been proved and validated by an empirical relation. The improved return on investment (ROI) and productivity shows the method of performing welding is feasible.Keywords
Lean Manufacturing, Cycle Time Reduction, Return on Investment, Productivity.- Impact of Lean Manufacturing on Improving Productivity of Auto Components Manufacturing Industry
Abstract Views :163 |
PDF Views:0
Authors
Affiliations
1 Dept. of Prod. Technology, M.l.T.Campus, Anna University, Chrompet, Chennai, IN
1 Dept. of Prod. Technology, M.l.T.Campus, Anna University, Chrompet, Chennai, IN
Source
Manufacturing Technology Today, Vol 8, No 5 (2009), Pagination: 20-26Abstract
The purpose of this paper is to develop an operationalized model, which can be used to access the changes taking place in an effort to introduce lean manufacturing system. We limited ourselves to the factors that concern the work organization in the manufacturing part of the company in order to develop an operational model of lean production. To bring the single piece flow assembly system, we have applied the principles of ergonomics, plant layout, and time study in this paper. These different principles have been elaborated using available theory behind the lean production system. The production system concept of process flow, plant layout, material flow, ergonomics and work place organization were integrated as a whole system in the plant. With the adaptation of above stated concepts, the assembly line became lean and also the productivity of the assembly line is comparably increased with the existing assembly system by 167%.- Prevalence of Depressive Symptoms among Incognizant Patients Visiting a Hospital
Abstract Views :295 |
PDF Views:0
Authors
Affiliations
1 Department of Public Health Dentistry, Thai Moogambigai Dental College and Hospital, IN
2 Thai Moogambigai Dental College and Hospital, IN
1 Department of Public Health Dentistry, Thai Moogambigai Dental College and Hospital, IN
2 Thai Moogambigai Dental College and Hospital, IN
Source
Indian Journal of Public Health Research & Development, Vol 11, No 1 (2020), Pagination: 207-211Abstract
This article depicts about depressive symptoms among patients visiting a hospital. Depression is the most common mental illness among people in many parts of the world. A person who suffers from depression experiences many symptoms which affects their day to day life to study the contributing factors associated with various levels of depression, a survey was conducted among patients visiting a private dental college at Chennai, Tamil Nadu. Convenience sampling technique was used for the survey. The patients were categorised according to their age, gender, education and employment status. Socio-economic status of the family head was also assessed in the survey. Marital status of an individual and any medical problems presented was also interviewed in the questionnaire. A list of PHQ-9 questionnaire was used to assess the associating factors among various level of depression.Keywords
Depression, Patients, Socio-Economic Status, Prevalence, Mental Health.- Analyzing The Software Quality In Image Processing Software In Industry Using Machine Learning
Abstract Views :144 |
PDF Views:0
Authors
Affiliations
1 Jaya Sakthi Engineering, IN
2 Department of Computer Science and Engineering, Jaya Engineering College, IN
3 Department of Computer Science and Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering, IN
1 Jaya Sakthi Engineering, IN
2 Department of Computer Science and Engineering, Jaya Engineering College, IN
3 Department of Computer Science and Engineering, Vel Tech High Tech Dr. Rangarajan Dr. Sakunthala Engineering, IN
Source
ICTACT Journal on Image and Video Processing, Vol 12, No 3 (2022), Pagination: 2674-2678Abstract
The ability of manufacturing organizations to generate defect-free, high-quality products is critical to their long-term success in the marketplace. Despite increased product diversity and complexity, as well as the necessity for cost-effective manufacturing, it is frequently important to conduct a thorough and reliable quality examination. There are bottlenecks in the manufacturing process because there are so many checks done. In this paper, we aim to automate the process of quality control in industries using a machine learning classifier that monitors the manufactured product namely the central processing unit via imaging technique. Development of a model with high quality control improves the productivity and efficacy of production that rejects the malignant and defect pieces from the supply chain. The use of imaging systems or high-speed camera enables the improvement of software quality, where the analysis is built using high clarity input images. The data processed by these imaging systems are transferred to the cyber-physical system for secured access within an organization. The results of classification of input images and process via machine learning improves the efficacy of the model over various machine learning models.Keywords
Software quality, Image Processing, Machine Learning, CyberReferences
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