The document discusses key topics in supply chain management. It outlines six major change drivers that have influenced the development of supply chain management, including globalization, technology, organization, empowered consumers, government policy, and sustainability. It also describes the evolution of supply chain management from procurement to integrated supply chain management. Major issues in supply chain management are identified as networks, complexity, inventory, information, costs, relationships, performance measurement, technology, transportation, security, and talent management.
Implement Consulting Group has summarised the strategic levers into five supply chain megatrends.
1.Multiple Supply Chains
2. Move On or Move Home
3. Green and Sustainable Supply Chains
4. Global Supply Chain Risk Management
5. Managing Supply Chain Complexity
Implement Consulting Group has summarised the strategic levers into five supply chain megatrends.
1.Multiple Supply Chains
2. Move On or Move Home
3. Green and Sustainable Supply Chains
4. Global Supply Chain Risk Management
5. Managing Supply Chain Complexity
This document explains how the omini channel supports and improves marketing and supply chain activities. It mainly involves
Drivers of supply chain network redesign, Process of comprehensive supply chain network design ,
Major locational determinants,
Modeling approaches for supply ,chain network design and
Omni-channel network design
1. Research Topic Super Computer Data MiningThe aim of this.docxketurahhazelhurst
1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilizes a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing. This purpose is embodied in the following objectives:
1. to develop a massively parallel approach for commonly used statistical and machine learning techniques for exploratory data analysis
1. to develop a massively parallel approach to the use of evolutionary computing techniques for feature creation and selection
1. to develop a massively parallel approach to the use of evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of ensemble machines for data modelling consisting of many well-known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to support the use of such advanced machine learning techniques with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is listed i.e. business aims and objectives are determined taking into consideration certain factors like the current background and future prospective.
Data exploration – Required data is collected and explored using various statistical methods along with identification of underlying problems.
Data preparation – The data is prepared for modeling by cleansing and formatting the raw data in the desired way. The meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying certain mathematical functions and modeling techniques. After the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a team of experts to check whether it satisfies business objectives or not.
Deployment – After evaluation, the model is deployed and further plans are made for its maintenance. A properly organized report is prepared with the summary of the work done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research paper
· Paper does not stick to the APA will result in 0 in the research paper
· Submission
. you have multiple submission to check you safe assignments
. The percentage accepted is 1%.
1. Research Topic Super Computer Data MiningThe aim of this.docxbraycarissa250
1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilizes a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing. This purpose is embodied in the following objectives:
1. to develop a massively parallel approach for commonly used statistical and machine learning techniques for exploratory data analysis
1. to develop a massively parallel approach to the use of evolutionary computing techniques for feature creation and selection
1. to develop a massively parallel approach to the use of evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of ensemble machines for data modelling consisting of many well-known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to support the use of such advanced machine learning techniques with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is listed i.e. business aims and objectives are determined taking into consideration certain factors like the current background and future prospective.
Data exploration – Required data is collected and explored using various statistical methods along with identification of underlying problems.
Data preparation – The data is prepared for modeling by cleansing and formatting the raw data in the desired way. The meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying certain mathematical functions and modeling techniques. After the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a team of experts to check whether it satisfies business objectives or not.
Deployment – After evaluation, the model is deployed and further plans are made for its maintenance. A properly organized report is prepared with the summary of the work done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research paper
· Paper does not stick to the APA will result in 0 in the research paper
· Submission
. you have multiple submission to check you safe assignments
. The percentage accepted is 1%.
Optimizing Global Brand Website Launches (Pharma)Best Practices
The global launch of a brand website represents a critical point in a new product's entry into the marketplace. Brand websites provide an important information portal for healthcare professionals, payers, patients, and advocacy groups.
Creating and launching a website that fulfills the diverse needs of key stakeholders while being mindful of regional differences in regulations and cultures are factors that can heavily influence how a new drug performs at launch.
This benchmark study probes current and evolving approaches for site development and optimization for brand websites as part of a global launch. The study also provides evidence-based benchmarks on what critical success factors are important for understanding and engaging key stakeholders, particularly physicians.
Retailers today are faced with unprecedented challenges ranging from shifting retail formats, overabundance of consumer choice, fast-changing technology, greater focus on quality and price to a tough economic climate. The result is that those who are not constantly innovating run the risk of falling behind. This white paper looks at the top five supply chain challenges that retailers face today and maps out a series of strategies to address these challenges based on research and direct experience in supporting retailers to maintain a competitive advantage in a highly competitive market.
Top 5 strategy of b2b supply chains trends and opportunitiesglobaltradeplaza498
B2B supply chains are experiencing significant transformations. As companies strive to stay competitive and meet the demands of their customers, they must adopt innovative strategies and leverage emerging trends. Here are the top five strategies for B2B supply chains, highlighting the trends and opportunities that can drive success.
When it comes to sustainability reporting, companies may feel like they’re in an increasingly uncomfortable public-private vice. On one side, consumers and shareholders are pressuring organizations to be better corporate citizens and increase transparency. Governments are establishing more reporting requirements as well, which will inevitably multiply through initiatives such as the recent Sustainable Innovation Forum at COP21.
No matter how you look at it, the call for climate action is coming
in surround sound. Integrated reporting is becoming more and
more mainstream.
The good news is that sustainability programs and reporting can
boost consumer confidence, shareholder esteem — and a company’s bottom line.
Next-generation supply chains Efficient, fast and tailored: Key findings from...Infinite Myriaads
The report identifies six key traits of highly effective supply chain managers. It shows how Leaders are moving ahead of the pack; tailoring their supply chains to customer needs and investing in next-generation capabilities while keeping  the focus on supply chains that are both fast and efficient. A key objective of the study is to link responses to key performance outcomes--separate the Leaders and Laggards.
This document explains how the omini channel supports and improves marketing and supply chain activities. It mainly involves
Drivers of supply chain network redesign, Process of comprehensive supply chain network design ,
Major locational determinants,
Modeling approaches for supply ,chain network design and
Omni-channel network design
1. Research Topic Super Computer Data MiningThe aim of this.docxketurahhazelhurst
1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilizes a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing. This purpose is embodied in the following objectives:
1. to develop a massively parallel approach for commonly used statistical and machine learning techniques for exploratory data analysis
1. to develop a massively parallel approach to the use of evolutionary computing techniques for feature creation and selection
1. to develop a massively parallel approach to the use of evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of ensemble machines for data modelling consisting of many well-known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to support the use of such advanced machine learning techniques with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is listed i.e. business aims and objectives are determined taking into consideration certain factors like the current background and future prospective.
Data exploration – Required data is collected and explored using various statistical methods along with identification of underlying problems.
Data preparation – The data is prepared for modeling by cleansing and formatting the raw data in the desired way. The meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying certain mathematical functions and modeling techniques. After the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a team of experts to check whether it satisfies business objectives or not.
Deployment – After evaluation, the model is deployed and further plans are made for its maintenance. A properly organized report is prepared with the summary of the work done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research paper
· Paper does not stick to the APA will result in 0 in the research paper
· Submission
. you have multiple submission to check you safe assignments
. The percentage accepted is 1%.
1. Research Topic Super Computer Data MiningThe aim of this.docxbraycarissa250
1. Research Topic: Super Computer Data Mining
The aim of this project is to produce a super-computing data mining resource for use by the UK academic community which utilizes a number of advanced machine learning and statistical algorithms for large datasets. In particular, a number of evolutionary computing-based algorithms and the ensemble machine approach will be used to exploit the large-scale parallelism possible in super-computing. This purpose is embodied in the following objectives:
1. to develop a massively parallel approach for commonly used statistical and machine learning techniques for exploratory data analysis
1. to develop a massively parallel approach to the use of evolutionary computing techniques for feature creation and selection
1. to develop a massively parallel approach to the use of evolutionary computing techniques for data modelling
1. to develop a massively parallel approach to the use of ensemble machines for data modelling consisting of many well-known machine learning algorithms;
1. to develop an appropriate super-computing infra-structure to support the use of such advanced machine learning techniques with large datasets.
Research Needs:
Problem definition – In the first phase problem definition is listed i.e. business aims and objectives are determined taking into consideration certain factors like the current background and future prospective.
Data exploration – Required data is collected and explored using various statistical methods along with identification of underlying problems.
Data preparation – The data is prepared for modeling by cleansing and formatting the raw data in the desired way. The meaning of data is not changed while preparing.
Modeling – In this phase the data model is created by applying certain mathematical functions and modeling techniques. After the model is created it goes through validation and verification.
Evaluation – After the model is created, it is evaluated by a team of experts to check whether it satisfies business objectives or not.
Deployment – After evaluation, the model is deployed and further plans are made for its maintenance. A properly organized report is prepared with the summary of the work done.
Research paper Policy
· APA format
. https://apastyle.apa.org/
. https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
· Min number of pages are 15 pages
· Must have
. Contents with page numbers
. Abstract
. Introduction
. The problem
4. Are there any sub-problems?
4. Is there any issue need to be present concerning the problem?
. The solutions
5. Steps of the solutions
. Compare the solution to other solution
. Any suggestion to improve the solution
. Conclusion
. References
· Missing one of the above will result -5/30 of the research paper
· Paper does not stick to the APA will result in 0 in the research paper
· Submission
. you have multiple submission to check you safe assignments
. The percentage accepted is 1%.
Optimizing Global Brand Website Launches (Pharma)Best Practices
The global launch of a brand website represents a critical point in a new product's entry into the marketplace. Brand websites provide an important information portal for healthcare professionals, payers, patients, and advocacy groups.
Creating and launching a website that fulfills the diverse needs of key stakeholders while being mindful of regional differences in regulations and cultures are factors that can heavily influence how a new drug performs at launch.
This benchmark study probes current and evolving approaches for site development and optimization for brand websites as part of a global launch. The study also provides evidence-based benchmarks on what critical success factors are important for understanding and engaging key stakeholders, particularly physicians.
Retailers today are faced with unprecedented challenges ranging from shifting retail formats, overabundance of consumer choice, fast-changing technology, greater focus on quality and price to a tough economic climate. The result is that those who are not constantly innovating run the risk of falling behind. This white paper looks at the top five supply chain challenges that retailers face today and maps out a series of strategies to address these challenges based on research and direct experience in supporting retailers to maintain a competitive advantage in a highly competitive market.
Top 5 strategy of b2b supply chains trends and opportunitiesglobaltradeplaza498
B2B supply chains are experiencing significant transformations. As companies strive to stay competitive and meet the demands of their customers, they must adopt innovative strategies and leverage emerging trends. Here are the top five strategies for B2B supply chains, highlighting the trends and opportunities that can drive success.
When it comes to sustainability reporting, companies may feel like they’re in an increasingly uncomfortable public-private vice. On one side, consumers and shareholders are pressuring organizations to be better corporate citizens and increase transparency. Governments are establishing more reporting requirements as well, which will inevitably multiply through initiatives such as the recent Sustainable Innovation Forum at COP21.
No matter how you look at it, the call for climate action is coming
in surround sound. Integrated reporting is becoming more and
more mainstream.
The good news is that sustainability programs and reporting can
boost consumer confidence, shareholder esteem — and a company’s bottom line.
Next-generation supply chains Efficient, fast and tailored: Key findings from...Infinite Myriaads
The report identifies six key traits of highly effective supply chain managers. It shows how Leaders are moving ahead of the pack; tailoring their supply chains to customer needs and investing in next-generation capabilities while keeping  the focus on supply chains that are both fast and efficient. A key objective of the study is to link responses to key performance outcomes--separate the Leaders and Laggards.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
Source Figure 1.1: Center for Supply Chain Research, Penn State University.
Source Figure 6.5: Adapted from Jacobs and Chase, Operation and Supply Chain Management 15th ed. (Boston, MA: McGraw-Hill Irwin, 2018). Reprinted with permission of McGraw-Hill Companies, Inc.
Source Figures 9.15 and 9.16: John J. Coyle, DBA. Used with permission.
Source Figures 9.15 and 9.16: John J. Coyle, DBA. Used with permission.
Source Figure 9.19: Robert A. Novack, Ph.D. Used with permission.
Source Figure 11.5: Brian J. Gibson, Ph.D. Used with permission.
Source Figure 11.3: Brian J. Gibson, Ph.D. Used with permission.
Source Figure 12.3: Copyright, C. John Langley Jr., Ph.D. Used with permission.
Source Figure 12.5: Copyright, C. John Langley Jr., Ph.D. Used with permission.
Source Figure 13.11: R. A. Novack, Center for Supply Chain Research, Penn State University (2015).
Source Figure 14.3: Brian J. Gibson, Ph.D. Used with permission.