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English
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Year
2022
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MOOC
Operations management deals with operational planning and control issues, and is needed in all sectors of the society. One of the challenges to operations manager is how to make use of the available resources in the best way for meeting a certain objective. Quantitative approaches are inevitably needed in tackling many of such problems. Operations Research (OR) deals with problem formulation and application of analytical methods to assist in decision-making of operational problems in planning and control. The techniques of OR are useful quantitative tools to assist operations managers, and has a wide applicability in engineering, manufacturing, construction, financial and various service sectors. Operations Research is an applied mathematics subject and is also a course in many engineering and management programmes. This course is designed for both students learning OR and learners who are practitioners in their respective professionals. The mathematical procedures for the OR techniques are introduced in details in the examples provided in the course. This helps learners to master the methodology and the techniques and apply them to achieve their goals through active learning. This course introduces two prominent OR techniques and their extended topics. The Simplex Method for Linear Programming (LP) has been considered one of the top 10 algorithms of the 20th century. LP is an optimization technique for solving problems such as finding the optimal product mix, production plan, and shipment allocation, in order to maximize the profir or minimize the cost. The Critical Path Method (CPM) is a popular technique employed by project managers in scheduling project activities. Some extended topics of CPM are also introduced to deal with certain special situations in project management. In reality, many systems operate under stochastic environment and the operational problems cannot be solved by the known analytical methods. To this end, the simulation approach is introduced in the last chapter of this course. Simulation is a powerful technique for tackling OR problems under such situations.
- Subjects:
- Statistics and Research Methods
- Keywords:
- Operations research
- Resource Type:
- MOOC
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MOOC
This award-winning course aims to sharpen your competitive edge in work and life. It empowers you with positive values and practical problem-solving skills, including creative strategies for addressing challenges from COVID-19. Enriched with interesting animations, a new success story and breakthrough pedagogies, this updated version (2.5) effectively helps you master knowledge and skills requisite for a successful life.
- Keywords:
- Creative thinking Learning ability Critical thinking
- Resource Type:
- MOOC
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MOOC
Everyone wishes to know the future!
Although we do not have the magic crystal ball to show us the future, we have interviewed more than forty (40+) international industrialists, academics, and business leaders. They are experts in their area and the drivers behind the industry. Our guests will share their views of the future and potential of the fashion industry with you.
During the interviews, we focused on the following questions:
What are the current challenges?
What are the new main directions in the coming five to ten (5 – 10) years?
What kind of new technologies will become popular?
Will there be any new business models (new ways of doing business)?
What role can a government play?
Will there be any ideology that may bring a big impact?
We fully understand that learners may face the obstacle of terminology and background. We will introduce the background of the fashion supply chain first. Then, we take the learners to attend the interviews week by week, sector by sector. Most importantly, the course content is bilingual in Chinese and English. Learners will enjoy our learning supports.
Suitable for students, consumers, anyone who is interested or working in the fashion business.
- Subjects:
- Fashion retailing and merchandising
- Keywords:
- Retail trade -- Management Clothing trade -- Management Business logistics
- Resource Type:
- MOOC
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MOOC
This course will equip you with the knowledge relevant to pulmonary diseases and broaden your understanding on the patient’s journey in healthcare from a holistic perspective – starting from symptoms emerge to the disease diagnosis and assessment, and finally, disease management in an interdisciplinary approach. In addition, as psychological intervention is also an important part in the all-round care of patients, this course also covers topics about the psychosocial needs of patients and caregivers.
What you'll learn:
The causes, signs and symptoms of common pulmonary diseases
Understand the psychosocial needs of patients and caregivers
Interpret the results of medical examinations for pulmonary diseases
Differentiate the roles of different healthcare professionals
Integrate the knowledge learnt from different disciplines in the management for patients with pulmonary diseases
- Subjects:
- Health Sciences
- Keywords:
- Lungs -- Diseases Lungs -- Diseases -- Patients Lungs -- Diseases -- Treatment
- Resource Type:
- MOOC
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MOOC
This data analytics course takes an interdisciplinary approach to demonstrate the data analytics process in the context of accounting and finance. The growing volume of both structured and unstructured data has pushed forward a more data-driven form of decision-making in accounting and finance. In order to keep up with the Big Data era advancements, accountants and finance professionals need to have a data analyst mindset to excel in their jobs. This course will illustrate different concepts of accounting and finance with the application of data analytics. It will not only help the learners to develop their skills to ask the right questions but also teach them how to master the data and use different tools like Excel and Tableau to analyze the data. In the end, the learners will be able to interpret the results and make their decisions effectively.
This course will use a simple framework that helps the learners to develop an analytical mindset. This framework (QDAR) has four major components:
1. Ask the right Q uestions to address an issue in accounting or finance contexts.
2. Understand the different data types and how to retrieve and clean D ata.
3. Conduct different data A nalyses to answer the questions
4. Communicate the R esults to the decision-makers using graphs, visualizations and reports.
The whole course will cover different aspects of the framework in conjunction with different types of analyses. There will be additional datasets for the verified learners through which they can practice what they have learned during the course.
- Subjects:
- Accounting and Finance
- Keywords:
- Accounting -- Data processing Finance -- Data processing
- Resource Type:
- MOOC
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MOOC
Aviation is essential for global business as it supports worldwide travelling and cargo transportation. Before COVID-19, the economic benefits generated by the industry across countries showed a growing trend. This course is aimed to provide learners with a broad understanding of airport services in different phases in terms of design and engineering. Learners will receive basic knowledge of how an airport operates. Key topics include the future perspective of air traffic control, air traffic flow management, airport management, facility planning, airport terminal design for the post-pandemic world and ground services.
- Subjects:
- Aeronautical and Aviation Engineering and Logistics
- Keywords:
- Airports -- Management Aeronautics Commercial -- Management Airlines -- Management
- Resource Type:
- MOOC
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MOOC
“Easy Vlogging – making Interactive Self-introduction Videos” is an online course for people to learn, in self-paced format, how to create effective job interview videos for either academic pursuit or career needs. With the contents learned from this course, it helps learners apply for dream jobs easier and more successfully, producing self-introduction videos with good visual quality, superior self-expression and professional presence.
The purpose of this course is to offer students with:
• An overview of digital video production, including script writing and other preparation works;
• An introduction on various video production techniques, including the use of camera, lighting and video editing techniques; and
• An understanding on the role of digital self-introduction video for interview purposes.
- Keywords:
- Video recordings -- Production direction
- Resource Type:
- MOOC
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Others
Learn more about finding a journal for publication, open access, predatory journals, your copyright as an author, social media in academics, enhancing your visbility, networking, tools for sharing and co-writing or research data management.
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Video
Convex Matrix Optimization (MOP) arises in a wide variety of applications. The last three decades have seen dramatic advances in the theory and practice of matrix optimization because of its extremely powerful modeling capability. In particular, semidefinite programming (SP) and its generalizations have been widely used to model problems in applications such as combinatorial and polynomial optimization, covariance matrix estimation, matrix completion and sensor network localization. The first part of the talk will describe the primal-dual interior-point methods (IPMs) implemented in SDPT3 for solving medium scale SP, followed by inexact IPMs (with linear systems solved by iterative solvers) for large scale SDP and discussions on their inherent limitations. The second part will present algorithmic advances for solving large scale SDP based on the proximal-point or augmented Lagrangian framework In particular, we describe the design and implementation of an augmented Lagrangian based method (called SDPNAL+) for solving SDP problems with large number of linear constraints. The last part of the talk will focus on recent advances on using a combination of local search methods and convex lifting to solve low-rank factorization models of SP problems.
Event date: 11/10/2022
Speaker: Prof. Kim-Chuan Toh (National University of Singapore)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Semidefinite programming
- Resource Type:
- Video
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Video
We introduce a Dimension-Reduced Second-Order Method (DRSOM) for convex and nonconvex (unconstrained) optimization. Under a trust-region-like framework, our method preserves the convergence of the second-order method while using only Hessian-vector products in two directions. Moreover; the computational overhead remains comparable to the first-order such as the gradient descent method. We show that the method has a local super-linear convergence and a global convergence rate of 0(∈-3/2) to satisfy the first-order and second-order conditions under a commonly used approximated Hessian assumption. We further show that this assumption can be removed if we perform one step of the Krylov subspace method at the end of the algorithm, which makes DRSOM the first first-order-type algorithm to achieve this complexity bound. The applicability and performance of DRSOM are exhibited by various computational experiments in logistic regression, L2-Lp minimization, sensor network localization, neural network training, and policy optimization in reinforcement learning. For neural networks, our preliminary implementation seems to gain computational advantages in terms of training accuracy and iteration complexity over state-of-the-art first-order methods including SGD and ADAM. For policy optimization, our experiments show that DRSOM compares favorably with popular policy gradient methods in terms of the effectiveness and robustness.
Event date: 19/09/2022
Speaker: Prof. Yinyu Ye (Stanford University)
Hosted by: Department of Applied Mathematics
- Subjects:
- Mathematics and Statistics
- Keywords:
- Convex programming Nonconvex programming Mathematical optimization
- Resource Type:
- Video