This document discusses the relationship between experimental economics and experimental computer science. It begins by noting that computer science and economic outcomes can be influenced by agents with different incentives, and traditional techniques alone may miss critical factors. Experimental economics over the past 30-40 years can benefit computer science. The document then provides definitions and examples of theoretical computer science, experimental computer science, and fields of computer science that use experiments. It concludes that aspects of experimental economics practice are worth considering for experimental computer scientists.
This paper discusses the several research methodologies that can
be used in Computer Science (CS) and Information Systems
(IS). The research methods vary according to the science
domain and project field. However a little of research
methodologies can be reasonable for Computer Science and
Information System.
Main points of this slide presentation:
1.What is statistics?
2.Application
3.Application of Statistics in Computer Science and Engineering
4.Machine learning’s Relation to statistics
5.Application of Statistics in Data mining
6.Data mining relation with Statistics
7.Outline of Applications
8.Some Outline of Application’s details are given below
Thank you
This slide is about Application of-statistics-in-CSE.Here you can helps from statistics application.This slide is very easy to understand and very helpful for engineering student.Specially for bangladeshi student.
ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models...Mahmoud Elbattah
ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models with Machine Learning
Paper presented at ACM 2018 Conference on Principles of Advanced Discrete Simulation (PADS)
https://dl.acm.org/citation.cfm?id=3200933
Authors:
Mahmoud Elbattah and Owen Molloy
National University of Ireland Galway
This lecture presented at Remote Sensing, Uncertainty Quantification and a Theory of Data Systems Workshop - Cahill Center, California Institute of Technology
Modern, large-scale simulation models are often based on the "laws of physics". Interpreting the outputs of these models nevertheless introduces a host of new challenges for uncertainty quantification and decision making. Unlike the traditional low-dimensional models in statistics or in applied maths, the state space of these simulation models is often large (10^7 D) and the components of the model state vector do not correspond to real-world observables. Nevertheless, in contexts like weather and climate, for example, such models sometimes provide significantly more information than traditional empirical models. Structural Model Error (SME) is the difference between the mathematical structure of the simulation model and the system that generates the observations (assuming that the system has a nontrivial mathematical description). In the absence of SME, reducing imprecision in parameter values and in the current state of the system is a daunting but tractable task, and forecasting deterministic systems takes on a probabilistic This presentation illustrates how SME, and the (almost certain) lack of topological conjugacy it implies, has significant impacts on what can be expected from simulation modelling. Challenges to various approaches of Uncertainty Quantification currently used in practice ("ensemble forecasting") and statistical methods exploiting a discrepancy function are demonstrated.
This paper discusses the several research methodologies that can
be used in Computer Science (CS) and Information Systems
(IS). The research methods vary according to the science
domain and project field. However a little of research
methodologies can be reasonable for Computer Science and
Information System.
Main points of this slide presentation:
1.What is statistics?
2.Application
3.Application of Statistics in Computer Science and Engineering
4.Machine learning’s Relation to statistics
5.Application of Statistics in Data mining
6.Data mining relation with Statistics
7.Outline of Applications
8.Some Outline of Application’s details are given below
Thank you
This slide is about Application of-statistics-in-CSE.Here you can helps from statistics application.This slide is very easy to understand and very helpful for engineering student.Specially for bangladeshi student.
ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models...Mahmoud Elbattah
ML-Aided Simulation: A Conceptual Framework for Integrating Simulation Models with Machine Learning
Paper presented at ACM 2018 Conference on Principles of Advanced Discrete Simulation (PADS)
https://dl.acm.org/citation.cfm?id=3200933
Authors:
Mahmoud Elbattah and Owen Molloy
National University of Ireland Galway
This lecture presented at Remote Sensing, Uncertainty Quantification and a Theory of Data Systems Workshop - Cahill Center, California Institute of Technology
Modern, large-scale simulation models are often based on the "laws of physics". Interpreting the outputs of these models nevertheless introduces a host of new challenges for uncertainty quantification and decision making. Unlike the traditional low-dimensional models in statistics or in applied maths, the state space of these simulation models is often large (10^7 D) and the components of the model state vector do not correspond to real-world observables. Nevertheless, in contexts like weather and climate, for example, such models sometimes provide significantly more information than traditional empirical models. Structural Model Error (SME) is the difference between the mathematical structure of the simulation model and the system that generates the observations (assuming that the system has a nontrivial mathematical description). In the absence of SME, reducing imprecision in parameter values and in the current state of the system is a daunting but tractable task, and forecasting deterministic systems takes on a probabilistic This presentation illustrates how SME, and the (almost certain) lack of topological conjugacy it implies, has significant impacts on what can be expected from simulation modelling. Challenges to various approaches of Uncertainty Quantification currently used in practice ("ensemble forecasting") and statistical methods exploiting a discrepancy function are demonstrated.
This paper discusses the several research methodologies that can
be used in Computer Science (CS) and Information Systems
(IS). The research methods vary according to the science
domain and project field. However a little of research
methodologies can be reasonable for Computer Science and
Information System.
This presentation is actually an orientation about the "computer science" branch.This presentation includes 2 videos.....
(i)Evolutions
(ii)Influential persons in history of computer
A preliminary survey on optimized multiobjective metaheuristic methods for da...ijcsit
The present survey provides the state-of-the-art of research, copiously devoted to Evolutionary Approach
(EAs) for clustering exemplified with a diversity of evolutionary computations. The Survey provides a
nomenclature that highlights some aspects that are very important in the context of evolutionary data
clustering. The paper missions the clustering trade-offs branched out with wide-ranging Multi Objective
Evolutionary Approaches (MOEAs) methods. Finally, this study addresses the potential challenges of
MOEA design and data clustering, along with conclusions and recommendations for novice and
researchers by positioning most promising paths of future research.
Machine Learning and Model-Based Optimization for Heterogeneous Catalyst Desi...Ichigaku Takigawa
2nd ICReDD International Symposium—Toward Interdisciplinary Research Guided by Theory and Calculation
Nov. 27 (wed) - Nov. 29 (fri), 2019
https://www.icredd.hokudai.ac.jp/event/1229
Mathematical models and algorithms challengesijctcm
This paper succinctly illustrates challenges encountered when modelling systems mathematically.
Mathematical modelling entirely entails math symbols, numbers and relations forming a functional
equation. These mathematical equations can represent any system of interests, also provides ease computer
simulations. Mathematical models are extensively utilized in different fields i.e. engineering, by scientists,
and analysts to give a clear understanding of the problem. Modelling contributed a lot since inversion of
the concept. Simple and complex structures erected as a result of modelling. In that sense modelling is an
important part of engineering. It can be referred to as the primary building block of every system. A
complex model however is not an ideal solution. Engineers have to be cautious not to discard all
information as this might render the designed model useless – as detailed in this paper the model should be
simple with all necessary and relevant data. Basically the purpose of this paper is to show the importance
and clearly explain in detail challenges encountered when modelling
ON SOFT COMPUTING TECHNIQUES IN VARIOUS AREAScscpconf
Soft Computing refers to the science of reasoning, thinking and deduction that recognizes and uses the real world phenomena of grouping, memberships, and classification of various quantities under study. As such, it is an extension of natural heuristics and capable of dealing with complex systems because it does not require strict mathematical definitions and
distinctions for the system components. It differs from hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role modelfor soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The main techniques in soft computing are evolutionary computing, artificial neural networks, and fuzzy logic and Bayesian statistics. Each technique can be used separately, but a powerful advantage of soft computing is the complementary nature of the techniques. Used together they can produce solutions to problems that are too complex or
inherently noisy to tackle with conventional mathematical methods. The applications of soft computing have proved two main advantages. First, it made solving nonlinear problems, in
which mathematical models are not available, possible. Second, it introduced the human knowledge such as cognition,
ecognition, understanding, learning, and others into the fields of
computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems. This paper highlights various areas of soft computing techniques.
Per l'ottavo incontro della serie “Complessità in azione – 8 leve per cambiare il mondo”, organizzata dal Complexity Institute in collaborazione con Complexity Education Project, Pier Luigi Gentili ha svolto un dialogo insieme a Luigi Ferrata sul tema:
La trasformazione eco-sistemica
Academia-to-Industry Transition of Search and Learning- Based Software Engine...Dr.Bestoun S. Ahmed
"Search and learning-based software engineering is about the exploitation of optimization and machine learning methods for the software engineering domain. The goal is to move the practices in software engineering from the human-based to machine-based problem-solving. Search and learning-based software engineering has been examined, researched, and developed in the last decade in the academia. The research output has shown many useful applications for the industry. However, while the area is promising, less effort has been made to transfer those discovered methods from academia to industry. This talk tries to explain the transition opportunities of search and learning-based software engineering from academia to industry. The talk will present many possibilities for applications."
This was an Inter Collegiate and a State Level Contest named SIGMA '08. Won a special prize for this paper. This research emphasized on how simple concepts of Mathematics helps into constructing complex mathematical models for space programming and their individual importance in real time applications.
Research in Computer Science and EngineeringOdiaPua1
Talks about Science and Research in the Computer Science and Engineering domain. The scientific foundations and methods of computer science and computer engineering.
Computation of Neural Network using C# with Respect to BioinformaticsSarvesh Kumar
Neural network is the emerging field in the era of globalization which is fully based on the concept of soft-computing technique and bioinformatics. In the competitive market of new development process, Bioinformatics play the vital role to give the process of integration aspect as multidisciplinary subject like- biological Science, medicine science, computer science, engineering, chemical science, physical science as well as mathematical science who gives the experiences of artificial activities of human behaviour in the form of software. Now a days neural Network and its multidimensional approach give the idea for solving bioinformatics problems to handle imprecision, uncertainty in large and complex search spaces. This paper gives the emphasis on multidimensional approaches of neural network with soft computing paradigm using C# in bioinformatics with integrative research methodology. The overall process of multidimensional approaches of bioinformatics neurons can also be understood with the help of flow chart and diagram is the major concerned.
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
This paper discusses the several research methodologies that can
be used in Computer Science (CS) and Information Systems
(IS). The research methods vary according to the science
domain and project field. However a little of research
methodologies can be reasonable for Computer Science and
Information System.
This presentation is actually an orientation about the "computer science" branch.This presentation includes 2 videos.....
(i)Evolutions
(ii)Influential persons in history of computer
A preliminary survey on optimized multiobjective metaheuristic methods for da...ijcsit
The present survey provides the state-of-the-art of research, copiously devoted to Evolutionary Approach
(EAs) for clustering exemplified with a diversity of evolutionary computations. The Survey provides a
nomenclature that highlights some aspects that are very important in the context of evolutionary data
clustering. The paper missions the clustering trade-offs branched out with wide-ranging Multi Objective
Evolutionary Approaches (MOEAs) methods. Finally, this study addresses the potential challenges of
MOEA design and data clustering, along with conclusions and recommendations for novice and
researchers by positioning most promising paths of future research.
Machine Learning and Model-Based Optimization for Heterogeneous Catalyst Desi...Ichigaku Takigawa
2nd ICReDD International Symposium—Toward Interdisciplinary Research Guided by Theory and Calculation
Nov. 27 (wed) - Nov. 29 (fri), 2019
https://www.icredd.hokudai.ac.jp/event/1229
Mathematical models and algorithms challengesijctcm
This paper succinctly illustrates challenges encountered when modelling systems mathematically.
Mathematical modelling entirely entails math symbols, numbers and relations forming a functional
equation. These mathematical equations can represent any system of interests, also provides ease computer
simulations. Mathematical models are extensively utilized in different fields i.e. engineering, by scientists,
and analysts to give a clear understanding of the problem. Modelling contributed a lot since inversion of
the concept. Simple and complex structures erected as a result of modelling. In that sense modelling is an
important part of engineering. It can be referred to as the primary building block of every system. A
complex model however is not an ideal solution. Engineers have to be cautious not to discard all
information as this might render the designed model useless – as detailed in this paper the model should be
simple with all necessary and relevant data. Basically the purpose of this paper is to show the importance
and clearly explain in detail challenges encountered when modelling
ON SOFT COMPUTING TECHNIQUES IN VARIOUS AREAScscpconf
Soft Computing refers to the science of reasoning, thinking and deduction that recognizes and uses the real world phenomena of grouping, memberships, and classification of various quantities under study. As such, it is an extension of natural heuristics and capable of dealing with complex systems because it does not require strict mathematical definitions and
distinctions for the system components. It differs from hard computing in that, unlike hard computing, it is tolerant of imprecision, uncertainty and partial truth. In effect, the role modelfor soft computing is the human mind. The guiding principle of soft computing is: Exploit the tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost. The main techniques in soft computing are evolutionary computing, artificial neural networks, and fuzzy logic and Bayesian statistics. Each technique can be used separately, but a powerful advantage of soft computing is the complementary nature of the techniques. Used together they can produce solutions to problems that are too complex or
inherently noisy to tackle with conventional mathematical methods. The applications of soft computing have proved two main advantages. First, it made solving nonlinear problems, in
which mathematical models are not available, possible. Second, it introduced the human knowledge such as cognition,
ecognition, understanding, learning, and others into the fields of
computing. This resulted in the possibility of constructing intelligent systems such as autonomous self-tuning systems, and automated designed systems. This paper highlights various areas of soft computing techniques.
Per l'ottavo incontro della serie “Complessità in azione – 8 leve per cambiare il mondo”, organizzata dal Complexity Institute in collaborazione con Complexity Education Project, Pier Luigi Gentili ha svolto un dialogo insieme a Luigi Ferrata sul tema:
La trasformazione eco-sistemica
Academia-to-Industry Transition of Search and Learning- Based Software Engine...Dr.Bestoun S. Ahmed
"Search and learning-based software engineering is about the exploitation of optimization and machine learning methods for the software engineering domain. The goal is to move the practices in software engineering from the human-based to machine-based problem-solving. Search and learning-based software engineering has been examined, researched, and developed in the last decade in the academia. The research output has shown many useful applications for the industry. However, while the area is promising, less effort has been made to transfer those discovered methods from academia to industry. This talk tries to explain the transition opportunities of search and learning-based software engineering from academia to industry. The talk will present many possibilities for applications."
This was an Inter Collegiate and a State Level Contest named SIGMA '08. Won a special prize for this paper. This research emphasized on how simple concepts of Mathematics helps into constructing complex mathematical models for space programming and their individual importance in real time applications.
Research in Computer Science and EngineeringOdiaPua1
Talks about Science and Research in the Computer Science and Engineering domain. The scientific foundations and methods of computer science and computer engineering.
Computation of Neural Network using C# with Respect to BioinformaticsSarvesh Kumar
Neural network is the emerging field in the era of globalization which is fully based on the concept of soft-computing technique and bioinformatics. In the competitive market of new development process, Bioinformatics play the vital role to give the process of integration aspect as multidisciplinary subject like- biological Science, medicine science, computer science, engineering, chemical science, physical science as well as mathematical science who gives the experiences of artificial activities of human behaviour in the form of software. Now a days neural Network and its multidimensional approach give the idea for solving bioinformatics problems to handle imprecision, uncertainty in large and complex search spaces. This paper gives the emphasis on multidimensional approaches of neural network with soft computing paradigm using C# in bioinformatics with integrative research methodology. The overall process of multidimensional approaches of bioinformatics neurons can also be understood with the help of flow chart and diagram is the major concerned.
Similar to experimental economics and experimental computer science (20)
Cracking the Workplace Discipline Code Main.pptxWorkforce Group
Cultivating and maintaining discipline within teams is a critical differentiator for successful organisations.
Forward-thinking leaders and business managers understand the impact that discipline has on organisational success. A disciplined workforce operates with clarity, focus, and a shared understanding of expectations, ultimately driving better results, optimising productivity, and facilitating seamless collaboration.
Although discipline is not a one-size-fits-all approach, it can help create a work environment that encourages personal growth and accountability rather than solely relying on punitive measures.
In this deck, you will learn the significance of workplace discipline for organisational success. You’ll also learn
• Four (4) workplace discipline methods you should consider
• The best and most practical approach to implementing workplace discipline.
• Three (3) key tips to maintain a disciplined workplace.
Improving profitability for small businessBen Wann
In this comprehensive presentation, we will explore strategies and practical tips for enhancing profitability in small businesses. Tailored to meet the unique challenges faced by small enterprises, this session covers various aspects that directly impact the bottom line. Attendees will learn how to optimize operational efficiency, manage expenses, and increase revenue through innovative marketing and customer engagement techniques.
RMD24 | Retail media: hoe zet je dit in als je geen AH of Unilever bent? Heid...BBPMedia1
Grote partijen zijn al een tijdje onderweg met retail media. Ondertussen worden in dit domein ook de kansen zichtbaar voor andere spelers in de markt. Maar met die kansen ontstaan ook vragen: Zelf retail media worden of erop adverteren? In welke fase van de funnel past het en hoe integreer je het in een mediaplan? Wat is nu precies het verschil met marketplaces en Programmatic ads? In dit half uur beslechten we de dilemma's en krijg je antwoorden op wanneer het voor jou tijd is om de volgende stap te zetten.
Premium MEAN Stack Development Solutions for Modern BusinessesSynapseIndia
Stay ahead of the curve with our premium MEAN Stack Development Solutions. Our expert developers utilize MongoDB, Express.js, AngularJS, and Node.js to create modern and responsive web applications. Trust us for cutting-edge solutions that drive your business growth and success.
Know more: https://www.synapseindia.com/technology/mean-stack-development-company.html
Putting the SPARK into Virtual Training.pptxCynthia Clay
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
Enterprise Excellence is Inclusive Excellence.pdfKaiNexus
Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
Discover the innovative and creative projects that highlight my journey throu...dylandmeas
Discover the innovative and creative projects that highlight my journey through Full Sail University. Below, you’ll find a collection of my work showcasing my skills and expertise in digital marketing, event planning, and media production.
The world of search engine optimization (SEO) is buzzing with discussions after Google confirmed that around 2,500 leaked internal documents related to its Search feature are indeed authentic. The revelation has sparked significant concerns within the SEO community. The leaked documents were initially reported by SEO experts Rand Fishkin and Mike King, igniting widespread analysis and discourse. For More Info:- https://news.arihantwebtech.com/search-disrupted-googles-leaked-documents-rock-the-seo-world/
Skye Residences | Extended Stay Residences Near Toronto Airportmarketingjdass
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Memorandum Of Association Constitution of Company.pptseri bangash
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
www.seribangash.com
Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
[Note: This is a partial preview. To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
Sustainability has become an increasingly critical topic as the world recognizes the need to protect our planet and its resources for future generations. Sustainability means meeting our current needs without compromising the ability of future generations to meet theirs. It involves long-term planning and consideration of the consequences of our actions. The goal is to create strategies that ensure the long-term viability of People, Planet, and Profit.
Leading companies such as Nike, Toyota, and Siemens are prioritizing sustainable innovation in their business models, setting an example for others to follow. In this Sustainability training presentation, you will learn key concepts, principles, and practices of sustainability applicable across industries. This training aims to create awareness and educate employees, senior executives, consultants, and other key stakeholders, including investors, policymakers, and supply chain partners, on the importance and implementation of sustainability.
LEARNING OBJECTIVES
1. Develop a comprehensive understanding of the fundamental principles and concepts that form the foundation of sustainability within corporate environments.
2. Explore the sustainability implementation model, focusing on effective measures and reporting strategies to track and communicate sustainability efforts.
3. Identify and define best practices and critical success factors essential for achieving sustainability goals within organizations.
CONTENTS
1. Introduction and Key Concepts of Sustainability
2. Principles and Practices of Sustainability
3. Measures and Reporting in Sustainability
4. Sustainability Implementation & Best Practices
To download the complete presentation, visit: https://www.oeconsulting.com.sg/training-presentations
"𝑩𝑬𝑮𝑼𝑵 𝑾𝑰𝑻𝑯 𝑻𝑱 𝑰𝑺 𝑯𝑨𝑳𝑭 𝑫𝑶𝑵𝑬"
𝐓𝐉 𝐂𝐨𝐦𝐬 (𝐓𝐉 𝐂𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
➢ 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
➢ SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
➢FreenBecky 1st Fan Meeting in Vietnam
➢CHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
➢ WOW K-Music Festival 2023
➢ Winner [CROSS] Tour in HCM
➢ Super Show 9 in HCM with Super Junior
➢ HCMC - Gyeongsangbuk-do Culture and Tourism Festival
➢ Korean Vietnam Partnership - Fair with LG
➢ Korean President visits Samsung Electronics R&D Center
➢ Vietnam Food Expo with Lotte Wellfood
"𝐄𝐯𝐞𝐫𝐲 𝐞𝐯𝐞𝐧𝐭 𝐢𝐬 𝐚 𝐬𝐭𝐨𝐫𝐲, 𝐚 𝐬𝐩𝐞𝐜𝐢𝐚𝐥 𝐣𝐨𝐮𝐫𝐧𝐞𝐲. 𝐖𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐛𝐞𝐥𝐢𝐞𝐯𝐞 𝐭𝐡𝐚𝐭 𝐬𝐡𝐨𝐫𝐭𝐥𝐲 𝐲𝐨𝐮 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚 𝐩𝐚𝐫𝐭 𝐨𝐟 𝐨𝐮𝐫 𝐬𝐭𝐨𝐫𝐢𝐞𝐬."
2. ABSTRACT
Many computer science research projects, system
outcomes may be influenced by computerized or
human agents with different economic incentives
Traditional computer science techniques, in isolation,
may overlook factors that are critical to the overall
outcome.
These efforts can benefit from the large body of work
that has been conducted in the field of experimental
economics in the last 30 to 40 years.
3. INTRODUCTION (1/3)
Computer science is a quickly evolving field covering
diverse areas such as computer networks,
nanotechnology, and computer architecture.
Observed differences between theory and fact can
motivate incremental progress or even create new
paths for overcoming strict beliefs held within
disciplines.
Formal methods of economic modeling and analysis
were extended to many fields in computer science.
4. INTRODUCTION (2/3)
Like computer science, economics has both theoretical
and experimental modes of inquiry.
Theoretical economics has fundamental limitations
that are relevant to the computer science researcher.
Many issues of concern to computer scientists cannot
meet the standard that results in the highest utility.
Although recent work in economics offers relaxations
from full rationality.
5. INTRODUCTION (3/3)
Economic theory, much like computer science theory,
necessarily leaves open questions regarding practical
deployment.
Economic experimentation provides insight into
realistic behaviors by human participants and their
expected impact on system outcomes.
A wide range of economics research is relevant to
computer science.
6. What is Experimental Economics?
Experimental Economics is an empirical tool that
enable economists to understand the extent to which an
individual's decision and behavior are affected by various
factor in controlled specifically designed environment.
Qualitative Method
Econometrics/statistical analysis of existing data or
new data collected through survey.
Experimental methods (lab or field)
Each has its relative strength/weaknesses
7. Cont’d
“The trick is to notice that economies created in the
laboratories might b very simple relative to those found
in nature, but they are just as real. Real people motivated
by real money make real decision, real mistakes and
suffer real frustration and delights because of their real
talents and real limitation.”
By Professor Charles Plott
8. What is Computer Science?
Many definitions
Study of algorithmic processes that describe and
transform information
Study of phenomena related to computers
Study of information structures
Study and management of complexity
Mechanization of abstraction
9. Cont’d
Mixture of
Engineering
Mathematics
Logic
Management
Generally CS is,
“Information theory concerned on transformation and
interpretation of information”
10. Scientific methods of computer
science
SimulationTheoretical
Computer Science
Experimental
11. What is theoretical computer
Science?
Subset of general computer science and mathematics
focus on more abstract or mathematical aspects of computing
Includes the theory of computation
Follows a very classical methodology of building theories
with rigid definitions of
Objects
operations
12. What is experimental computer
science?
Three components define experimental science
Observation
Hypothesis testing
Reproducibility
14. Fields of computer science use
experiments
Search
Automatic theorem proving
Planning
NP complete problems
Natural language
Vision
Games
Machine learning
15. CONCLUSSION
All studies presented here follow the outlined principles
closely.
Some aspects of the studies could be improved with a
different manipulation of treatment variables and more
thorough exploration of hypotheses in advance.
Many aspects of experimental practice in economics are
worth considering for experimental computer scientists
The relationship between experimental economics and
computer science is not a one-way street
Experimental economics is just one helpful addition to the
experimental computer science toolkit.
