Intensive Data and Knowledge-Driven Approach for Sustainability Analysis: Application to Lignocellulosic Waste Valorization Processes

2021 ◽  
Author(s):  
Jean-Pierre Belaud ◽  
Nancy Prioux ◽  
Claire Vialle ◽  
Patrice Buche ◽  
Sébastien Destercke ◽  
...  
Keyword(s):  
Waste Valorization ◽  
Lignocellulosic Waste ◽  
Sustainability Analysis ◽  
Analysis Application

Old Enzymes at the Forefront of Lignocellulosic Waste Valorization

2020 ◽  
pp. 57-78
Author(s):  
Simona Giacobbe ◽  
Cinzia Pezzella ◽  
Giovanni Sannia ◽  
Alessandra Piscitelli
Keyword(s):  
Waste Valorization ◽  
Lignocellulosic Waste

Reduced model error analysis “application to synchronous machines"

1994 ◽  
Vol 4 (10) ◽  
pp. 1999-2012 ◽  
Author(s):  
Nabil Derbel ◽  
Mohamed B.A. Kamoun ◽  
Michel Poloujadoff
Keyword(s):  
Error Analysis ◽  
Model Error ◽  
Synchronous Machines ◽  
Reduced Model ◽  
Analysis Application

DTI data analysis: application of fiber tracking to group averaged data sets

2010 ◽  
Vol 41 (01) ◽  
Author(s):  
HP Müller ◽  
A Unrath ◽  
A Riecker ◽  
AC Ludolph ◽  
J Kassubek
Keyword(s):  
Data Analysis ◽  
Fiber Tracking ◽  
Data Sets ◽  
Analysis Application

STUDY ON WET PROCESSING OF BLOCK CHILLY

2013 ◽  
Vol 3 (1) ◽  
pp. 45-50
Author(s):  
Dwi Dian Praptanto ◽  
Kurnia Herlina Dewi ◽  
Bosman Sidebang
Keyword(s):  
Water Content ◽  
Production Method ◽  
Time Data ◽  
Time Duration ◽  
Drying Time ◽  
Significance Level ◽  
Randomized Design ◽  
Wet Processing ◽  
Analysis Application ◽  
Lower Water Content

The purpose of this study is to examine the effect of drying time in weight and water content, combination effect of drying time and size of the material, and consumer acceptance to the product in the wet processing of chili blocks production. Method used in the research is completely randomized design (CRD) with two factorials are material size and drying time. Data were analyzed using ANOVA and further analysis using DMRT at 5% significance level. Organoleptic test result was analyzed using the Kruskal-Wallis and Tukey test for further analysis. Application of the equal drying time to two different size of material: rough and finest block chili, showed the result that water content of the rough block chili is lower than the finest block chilli. Application of the different drying time duration to the same size of chili showed the lower water content with increasing duration of drying time. The water content of the material tends to decrease with increasing duration of drying time. The level of consumer’s preferences to the product of wet processing of chili blocks production is equal for scents, but it’s different for color, texture and overall preferences.

Failure Analysis of Broken Stitch Bonds in TSSOP Packages Using Scanning Acoustic Microscopy (SAM) and Time Domain Reflectometry (TDR)

2004 ◽  
Author(s):  
Bilal Abd-AlRahman ◽  
Corey Lewis ◽  
Todd Simons
Keyword(s):  
Failure Analysis ◽  
Mechanical Stress ◽  
Time Domain ◽  
Open Circuit ◽  
Time Domain Reflectometry ◽  
Acoustic Microscopy ◽  
Scanning Acoustic Microscopy ◽  
Root Cause ◽  
Analysis Application

Abstract A failure analysis application utilizing scanning acoustic microscopy (SAM) and time domain reflectometry (TDR) for failure analysis has been developed to isolate broken stitch bonds in thin shrink small outline package (TSSOP) devices. Open circuit failures have occurred in this package due to excessive bending of the leads during assembly. The tools and their specific application to this technique as well as the limitations of C-SAM, TDR and radiographic analyses are discussed. By coupling C-SAM and TDR, a failure analyst can confidently determine whether the cause of an open circuit in a TSSOP package is located at the stitch bond. The root cause of the failure was determined to be abnormal mechanical stress placed on the pins during the lead forming operation. While C-SAM and TDR had proven useful in the analysis of TSSOP packages, it can potentially be expanded to other wire-bonded packages.

Combinatorial Double Auction Based Meta-scheduler for Medical Image Analysis Application in Grid Environment

2020 ◽  
Vol 13 (5) ◽  
pp. 999-1007
Author(s):  
Karthikeyan Periyasami ◽  
Arul Xavier Viswanathan Mariammal ◽  
Iwin Thanakumar Joseph ◽  
Velliangiri Sarveshwaran
Keyword(s):  
Image Analysis ◽  
Medical Image ◽  
Medical Image Analysis ◽  
Grid Resource ◽  
Resource Broker ◽  
Analysis Application ◽  
Local Grid ◽  
Grid Resource Broker ◽  
Global Grid ◽  
Grid Site

Background: Medical image analysis application has complex resource requirement. Scheduling Medical image analysis application is the complex task to the grid resources. It is necessary to develop a new model to improve the breast cancer screening process. Proposed novel Meta scheduler algorithm allocate the image analyse applications to the local schedulers and local scheduler submit the job to the grid node which analyses the medical image and generates the result sent back to Meta scheduler. Meta schedulers are distinct from the local scheduler. Meta scheduler and local scheduler have the aim at resource allocation and management. Objective: The main objective of the CDAM meta-scheduler is to maximize the number of jobs accepted. Methods: In the beginning, the user sends jobs with the deadline to the global grid resource broker. Resource providers sent information about the available resources connected in the network at a fixed interval of time to the global grid resource broker, the information such as valuation of the resource and number of an available free resource. CDAM requests the global grid resource broker for available resources details and user jobs. After receiving the information from the global grid resource broker, it matches the job with the resources. CDAM sends jobs to the local scheduler and local scheduler schedule the job to the local grid site. Local grid site executes the jobs and sends the result back to the CDAM. Success full completion of the job status and resource status are updated into the auction history database. CDAM collect the result from all local grid site and return to the grid users. Results: The CDAM was simulated using grid simulator. Number of jobs increases then the percentage of the jobs accepted also decrease due to the scarcity of resources. CDAM is providing 2% to 5% better result than Fair share Meta scheduling algorithm. CDAM algorithm bid density value is generated based on the user requirement and user history and ask value is generated from the resource details. Users who, having the most significant deadline are generated the highest bid value, grid resource which is having the fastest processor are generated lowest ask value. The highest bid is assigned to the lowest Ask it means that the user who is having the most significant deadline is assigned to the grid resource which is having the fastest processor. The deadline represents a time by which the user requires the result. The user can define the deadline by which the results are needed, and the CDAM will try to find the fastest resource available in order to meet the user-defined deadline. If the scheduler detects that the tasks cannot be completed before the deadline, then the scheduler abandons the current resource, tries to select the next fastest resource and tries until the completion of application meets the deadline. CDAM is providing 25% better result than grid way Meta scheduler this is because grid way Meta scheduler allocate jobs to the resource based on the first come first served policy. Conclusion: The proposed CDAM model was validated through simulation and was evaluated based on jobs accepted. The experimental results clearly show that the CDAM model maximizes the number of jobs accepted than conventional Meta scheduler. We conclude that a CDAM is highly effective meta-scheduler systems and can be used for an extraordinary situation where jobs have a combinatorial requirement.

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