Dataset nghiên cứu (liên hệ)
Danh mục tài liệu tham khảo
Trung Quốc, Bắc Kinh – Lịch sử, Văn hóa, Khoa học
Mỗi khi có dịp ra nước ngoài công tác, mình lại muốn cố gắng dành 1-2 ngày để khám phá và trải nghiệm văn hóa, lịch sử, xã hội của quốc gia/ thành phố mà mình ghé thăm. Và lần này cũng vậy, tại Bắc Kinh – Trung Quốc vào tháng 07/2025, mình đã dành ra cả 1 ngày để khám phá hai bảo tàng làm mình Wow vô cùng.
Đó là: Bảo tàng Khoa học Bắc Kinh (China Science and Technology Museum) và Bảo tàng Khảo cổ Bắc Kinh (Chinese Archaeological Museum).
Vì bài blog này là góc nhìn/ cảm nhận của mình về cách mà chính phủ Trung Quốc đã xây dựng phương thức truyền tải Lịch sử, Văn hóa, Khoa học cực kỳ khiến mình khâm phục và rất mê. Nên là… mình sẽ không nói quá nhiều về những vật phẩm trưng bày hay các khu vực tham quan, vì thật sự nó có quá là nhiều thứ để nói và bàn đến.
Về phía Bảo tàng Khoa học, họ tập trung trình bày về các thành tựu trong mọi lĩnh vực khoa học cổ đại như Y học cổ truyền (châm cứu, thuốc từ cây cỏ,…), Khí tượng học, Chiêm tinh học, và Thiên văn học (đồng hồ, bản đồ sao,…), Kiến trúc nhà cửa/ cung điện, cho đến những ngành nghiên cứu hiện đại như Y học hiện đại, Hàng không vũ trụ, Khoa học máy tính, Công nghệ LED,…
Điều đó cho thấy họ trân trọng và gìn giữ những thành tựu mà họ tự hào. Một chuỗi dài lịch sử cả vài ngàn năm, biết bao nhiêu là phát minh, bao nhiêu là ứng dụng làm nền tảng và tầng tầng lớp lớp những những phát minh dựa vào những ý tưởng được thử nghiệm ở những đời trước kia. Có vẻ như… họ trân trọng tất cả và không bỏ đi thành tựu gì. Và là một người thích đọc lịch sử, mình lại cảm thấy hiểu rõ hơn về bối cảnh ra đời những phát minh đó, hiểu nó phục vụ cho cái gì, và tại sao lại cần.
Mình khá ấn tượng về phần Chiêm tinh dự báo tương lai đi (aka: Tử Vi ấy). Về cơ bản thì họ đi từ bản đồ sao và một loạt các thống kê nhân khẩu có vẻ là đã được thực hiện, mà bản đồ sao được tạo ra ban đầu để theo dõi thời tiết, mùa màng. Mà để có được bản đồ sao thì sẽ cần có các thiết bị đo đạc. Mà đo đạc một hồi thì có vẻ là họ cũng có kỳ vọng mọi thứ “có thể dự đoán được”, “có thể chuẩn bị được”, “có thể lặp lại” và mang tính “chu kỳ”. Nên là yeah, đối với mình, đó là đỉnh cao của mọi sự liên quan luôn. Và sự liên quan đó lại mang một cái “tính tự chủ”, và ước muốn “làm chủ thiên nhiên” của con người Trung Hoa. Đúng thật, mọi thứ đều có lý do của nó.
Bước qua phía bảo tàng Khảo cổ học cách đó không xa, mình bước vào ngàn năm lịch sử với những hiện vật mang tính “văn hóa”, “đời sống” nhiều hơn. Lần mò từ thời kỳ đồ đá (Stone Age), đồ đồng (Bronze Age), đến những thời kỳ Xuân Thu chiến quốc, rồi các triều đại phong kiến Trung Hoa, và thời kỳ nội chiến, đến khi Đảng Cộng Sản Trung Quốc lãnh đạo nhà nước.
Một vài thắc mắc mà mình được giải đáp như… mình dần hiểu được cách mà chữ viết Trung Quốc được hình thành, cách mà ngữ nghĩa được ẩn sâu trong từng con chữ; hay là “vì sao hệ thống ly rượu của Trung Quốc lại luôn là kiểu 3 chân?”, hay “quá trình phát triển triết lý tư tưởng từ thời Nho giáo đến Chủ nghĩa Xã hội Trung Hoa”,… mọi thứ hiển hiện rõ ngay trước mắt mà chỉ cần mình đến đó, đọc thông tin bằng cả tiếng Anh và tiếng Trung (Translator) và liên kết mọi dữ kiện lại, và… mình wow.
Cách mà thành phố Bắc Kinh tạo ra những không gian lưu trữ lịch sử, văn hóa, khoa học này làm mình nể lắm. Họ thật sự có tâm với những gì mà tổ tiên họ đã để lại cho họ. Và họ biết cách để truyền đạt, biết cách để kích thích sự tò mò của một người nước ngoài tìm hiểu về đất nước và những gì hay, quý nhất của họ. Họ luôn có một cái theme – theme về sự tự hào trong dòng chảy lịch sử xuyên suốt. Và mình thích điều đó.
Nếu có dịp ghé Bắc Kinh, bạn thử ghé thăm 2 bảo tàng này thử nhen.
- Bảo tàng Khoa học Bắc Kinh (China Science and Technology Museum) và
- Bảo tàng Khảo cổ Bắc Kinh (Chinese Archaeological Museum)
TLH MASLOW
FYI
LV2-P1: A good HEART
Hello, my fellow Toastmasters and friends,
For today’s project, my focus is on “Understanding Your Leadership Style.”
After completing the 48-question Toastmasters leadership assessment, I arrived at an interesting result:
As you can see, my scores across the top five leadership styles are almost the same. So, what exactly is my leadership style? Is there any evidence to support this unusual result?
I believe a reflection from November 2024 might offer some clues.
My Journey: A Quick Snapshot
To give you some context, here’s a brief look at my professional journey (https://www.linkedin.com/in/henryduclai/):
Education journey
- 2014 – 2015: International Business Student @ FTU HCM
- 2016 – 2019: Cyber Security Student @ FPT HCM
- 2020 – 2023: MSc. in Computer Science @ VNU HCMUT
- 2025 – 2027: Clinical Psychology Student @ VNU HCM USSH
Professional journey
- 2017 – 2019: Software Developer @ Pizitech
- 2017 – 2018: Software Developer & Solution Architect @ Savills Vietnam
- 2019 – 2023: Individual Consultant ➡️ Data Science Manager @ Unilever Vietnam
- 2023 – Present: Global Data Science Manager @ Unilever Global
If you Google “LẠI TRUNG MINH ĐỨC,” you might even find some articles written about me.
The Question: How Did I Become a Manager?
Some people say my journey is too hard to believe. Even I was surprised during a recent reflection. How did a fresh graduate become a consultant and then a manager in such a short time—without formal management training? What made the leadership team trust me with such responsibilities?
For years, I didn’t have an answer. I never questioned why I was promoted so quickly. If anyone asked, I would simply say, “I delivered technical work fast, achieved great cost savings, and was rewarded with a management role.”
But then… November 2024 happened.
The Defining Moment
When my company’s restructuring plan began affecting my colleagues globally, I felt an urge deep in my heart: “I have to be there.”
I booked urgent flights with my own pocket to India, Thailand, Singapore, and Indonesia, telling myself:
“I can’t change reality, but I can sit with them. I can listen. I can share their pain.”
During these trips, I had heartfelt conversations with colleagues about leadership, career struggles, and the emotional toll of management. Surprisingly, many of them told me:
“Duc, you were born to be a leader.”
The Realization: What Makes a Leader?
One conversation stood out:
Friend: “Why are you physically here?”
Me: “I think virtual connections won’t truly help. I need to be here.”
Friend: “But why do you care?”
Me: “I’ve been through this. I know how painful it is. I just hope my presence makes it a little easier for you.”
Friend: “That’s interesting. At work, you’re like an assassin—fighting vendors for every dollar. But now, you’re this warm-hearted person. Which one is the real you?”
Me: “Both. They are all me.”
Friend: “Exactly. That’s why you’re a good leader. You’re flexible, knowledgeable, tough when needed, and compassionate when it matters. And most importantly, you have a good heart.”
That moment was my “Aha!”
The Key Takeaway: Leadership is Fluid
Leadership isn’t about fitting into one category. It’s about adapting to what’s needed in the moment. No wonder my leadership assessment results were evenly distributed!
I can be Democratic, Coaching, Authoritative, Innovative, or Affiliative—whenever necessary. As long as my heart and mind align with a meaningful purpose, I can lead effectively in any situation.
Final Thoughts
My fellow Toastmasters and friends,
This leadership assessment is just for your reference. Don’t limit yourself into the result of this. You are not just one color—you can be any shade you choose. As long as you stay true to your core values and lead with a good heart, everything will work out.
And remember: Leadership is an ART. That’s why you need a good HEART to master it.
Thank you.
LV1-P3: Stop Feeling Guilty on Your Money
In May, I met a friend, and we talked about relationships.
- She said to me, “You’re a manager with a great reputation. Your aura at work is so confident, but why are you so shy and vulnerable in your personal life?”
- I replied, “Oh wow! You’ve noticed what I’ve just figured out myself. I panic when I talk to someone I’m interested in, but I have no idea how to fix it.”
- She gave me this advice: “Find the root cause of your confidence at work and your lack of confidence in life. Solve that, and soon enough, you’ll have a girlfriend.”
Her strong words stuck with me, pushing me to look deeper into my life and discover what was holding me back.
Today, after months of researching and practicing confidence, I want to share what I’ve learned. Confidence isn’t about fancy clothes, accessories, or dining at the most expensive restaurants. It isn’t something you can buy; it’s something you own by making choices that feel right and comfortable for you.
Take CEOs from companies like Microsoft, Amazon, and Facebook. You’ll see them walking around in casual clothes, eating hotdogs. They can switch from street food to luxury dining in an instant without a second thought. I’m not as rich as those CEOs, but I’m not poor like I once was either. So why did I feel guilty spending just 200 USD a month on myself, but not guilty when I lost 20,000 USD in the crypto market?
Let me take you through an experiment I conducted on myself last 3 weeks.
- I planned a 5-day trip to Korea for IU concert.
- I booked flights and hotels, not based on the cheapest deals, but on what felt comfortable and balanced for my income.
- I’ve loved capturing photos since high school, so I bought myself a brand-new Nikon camera.
- I ate at a mid-tier restaurant, a family restaurant, and at convenience stores.
But then, guilt crept in. When I ate at the mid-tier restaurant, I felt guilty… I thought, “Why didn’t I just find a cheaper option?” I felt sad when I couldn’t claim tax on my camera… and when I took a taxi to my hotel during heavy rain, I felt guilty again, because I could’ve walked with my heavy luggage.
That’s when I realized something: Whenever my comfort level in spending is lower than someone else’s, I lose my confidence. But why? Confidence should come from my financial situation and reality, not just from emotions or old family standards or others priviledges.
- Was I happy when I captured those photos? Yes, I was thrilled!
- Was I happy eating at the mid-tier restaurant? No, because I felt lonely looking at other couples.
- But when I ate at a convenience store? Yes! I felt like I was in a Korean drama, and I could even chat with others.
- And when the taxi driver helped me find my hotel in the rain? Oh yes! I was so grateful. I would have been sick if I hadn’t taken that taxi.
So, the guilt I felt was simply about losing a bit of money, amplified by my feelings of loneliness and the weight of old family expectations. But here’s the truth: I can be happy with my choices and spending, as long as they align with my reality. And when I’m happy and satisfied, that’s when my confidence grows.
Next time you feel guilty about spending on yourself, ask: Is it the expense, or is it how I feel about myself? True confidence is knowing you’re worth every cent. In the end, it’s not the price tag that defines your confidence, but how comfortable you are with your choices.
Here are some of my photos.
Toastmaster LV1 P2: I AM MY OWN LIGHT
Back in 2008, I was a secondary school student from an average-income family. My mom worked hard as a tailor at home, and my dad worked long hours at a factory far away. They worked more than 8 hours a day, hoping that my sister and I would study hard and escape poverty. While my sister excelled at school and received praise everywhere, I struggled and was often at the bottom of the class due to my skewed learning. My parents were very disappointed. They would yell at me when scorecards came, compare me to my sister constantly, and even stopped me from making friends, thinking it was a waste of time.
A little boy in that stressful environment felt very small, and his soul grew darker and darker.
In 2010, my dad passed away from lung cancer, and my mom had to step up to handle all the family expenses. Despite her grief, she kept working even harder, more than 12 hours a day. One year later, while my sister successfully entered a top university, I failed the entrance exam for a gifted high school and continued to disappoint my mom. During my unhappy high school years, filled with exhaustion, boredom, isolation, and a one-sided, ignorant relationship, I kept performing poorly. Because of that, my mom often said hurtful things, and one of them I still remember: “It would have been better if you were never born, truly unfortunate.”
A high school boy in that frustrating environment felt useless and as if nobody needed him. His soul was full of anger and sadness, and he wanted to end his miserable life.
In early 2013, I ended up in the hospital for a week after fainting at home. I had an irregular heartbeat, and the doctor warned me, “You could die if you do anything that triggers your heart.” Feeling hopeless in life, I took his warning and interpreted it in a dark way. I decided to end my life after receiving the poor results of the first semester. I took an 80km bicycle ride, hoping my heart would stop along the way. During the trip, I had a near-death experience. I fainted on the side of the road, and when I woke up, the pain and doubt were overwhelming. I told myself in that lonely moment, “It’s too painful to die. I can’t endure this pain. Living in this miserable life is better than this pain. I cannot die, but I can’t continue the current life. I need to live in another way.” It took me a while to stand up, and yes, I decided to continue my journey slowly and carefully, to reach the destination with the ‘new me’—who had just realized: HE CAN CONTROL HIS CHOICES.
Leveraging that new life experience, I felt that: “I have many options to choose from. I can decide my own life, not my family. No one could affect me if I had a strong shield. I AM MY OWN LIGHT; I can be my own supporter for what I choose to do, while waiting for the greater light to come.” With this new mindset, I gained confidence in what I was doing, found the courage to make new friends, and found myself better, stronger, and reasons to live on. A year later, I got into two top universities, which was a big achievement for me, and amazingly, my mom started seeing me differently—no longer as a loser in the family.
To close this speech, I AM MY OWN LIGHT is the important lesson I learned. This inner light keeps me going, gives me energy and hope, and helps me wait for stronger lights that will bring a better future.
And to you, my fellow Toastmasters, don’t give up in your darkest times. BE YOUR OWN LIGHT in the dark and keep hoping for better days and willingly asking for support. You will surely get it and overcome it.
Thank you.
Tutorial [Basic]: Vectorization and Pandas Iterrows, Apply, and Performance Comparison
In this tutorial, we will explore the concept of vectorization and compare it with two common alternatives, iterrows() and apply(), in the context of working with data in Pandas. We will also assess the performance differences between these methods to understand when to use each one.
Table of Contents
- Introduction
- Vectorization
- Using
iterrows() - Using
apply() - Performance Comparison
- Conclusion
1. Introduction
Pandas is a powerful library for data manipulation in Python. It provides various ways to work with data, and choosing the right method can significantly impact the performance of your code. In this tutorial, we’ll focus on vectorization and compare it with two other common techniques: iterrows() and apply().
What is Vectorization?
Vectorization is a technique in Pandas that leverages the underlying NumPy library to perform operations on entire arrays or Series, rather than iterating through individual elements. It is generally the most efficient way to work with data in Pandas.
2. Vectorization
Vectorized operations in Pandas can be applied to entire columns or Series, which results in faster and more concise code. For example, to add two columns element-wise, you can do:
import pandas as pd
# Create a DataFrame
df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
# Vectorized addition
df['C'] = df['A'] + df['B']
This code adds the ‘A’ and ‘B’ columns element-wise and stores the result in a new column ‘C’. No explicit iteration is required, which makes the code more efficient.
3. Using iterrows()
The iterrows() method allows you to iterate over rows in a DataFrame, and you can apply custom functions to each row. However, it is not as efficient as vectorized operations for large datasets.
# Using iterrows() to add columns element-wise
for index, row in df.iterrows():
df.at[index, 'C'] = row['A'] + row['B']
While iterrows() can be convenient for specific cases, it is less efficient than vectorization because it requires iteration over rows.
4. Using apply()
The apply() method allows you to apply a function to each element of a Series or DataFrame. It can be more efficient than iterrows(), but it may still be slower than vectorization.
# Using apply() to add columns element-wise
df['C'] = df.apply(lambda row: row['A'] + row['B'], axis=1)
The apply() method can be more readable than iterrows(), but for simple element-wise operations, vectorization is usually faster.
5. Performance Comparison
To compare the performance of these three methods, we can use the timeit library to measure the execution time for each approach. Let’s see an example:
import pandas as pd
import numpy as np
import timeit
# Create a large DataFrame
df = pd.DataFrame({'A': np.random.randint(1, 100, 10000),
'B': np.random.randint(1, 100, 10000)})
# Vectorized addition
def vectorized_addition():
df['C'] = df['A'] + df['B']
# Using iterrows()
def iterrows_addition():
for index, row in df.iterrows():
df.at[index, 'C'] = row['A'] + row['B']
# Using apply()
def apply_addition():
df['C'] = df.apply(lambda row: row['A'] + row['B'], axis=1)
# Measure execution time (number = 1 means: run 1 time)
vectorized_time = timeit.timeit(vectorized_addition, number=1)
iterrows_time = timeit.timeit(iterrows_addition, number=1)
apply_time = timeit.timeit(apply_addition, number=1)
print(f"Vectorized Time: {vectorized_time}")
print(f"iterrows Time: {iterrows_time}")
print(f"apply Time: {apply_time}")
This code compares the execution times of vectorization, iterrows(), and apply() for adding two columns in a large DataFrame. If you run those code on Google Colab, you should get similar output with me.
Vectorized Time: 0.001311236000219651
Iterrows Time: 0.7449517189998005
Apply Time: 0.1326701759999196
Based on the result, the performance order is Iterrows (0.74s – slowest), Apply (0.13s which improves 7x), then Vectorization (0.001s which improve 740x vs. Iterrows, and 100x vs. Apply).
6. Conclusion
In conclusion, vectorization is the most efficient way to perform operations on Pandas DataFrames. It is faster and more concise compared to iterrows() and apply(). However, there may be cases where iterrows() or apply() are more appropriate, especially when dealing with complex operations that cannot be easily vectorized. Always consider the trade-off between performance and code readability when choosing a method to work with your data in Pandas.
In the next tutorial, I will show the detail comparison on the common case: Feature Engineering on Date data.
[Translate] Quy định của Bộ Nội Vụ Pháp về giấy chứng nhận du lịch quốc tế (Certificate of international travel)
Cập nhật ngày 23/7/2021
Xin chào các bạn,
Để chuẩn bị cho một hành trình bay đến Ireland an toàn và suôn sẻ, mình mạn phép dịch thông tin từ trang web của Bộ Nội Vụ Pháp quy định về xuất nhập cảnh, cho các bạn nào chọn bay đường bay quá cảnh sang Pháp nhé 😊
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Vài tips chuẩn bị cho các bạn DHS Công Giáo trước khi đi du học
Xin chào các bạn,
Đối với các bạn DHS Công Giáo khi đi du học, mối quan tâm của các bạn và gia đình không chỉ là việc học hàng ngày, mà còn về việc sẽ giữ lễ Chúa Nhật và các ngày lễ buộc như thế nào nữa. Có phải các bạn đã từng lo lắng rằng khi qua đất nước mới thì “mình sẽ đi lễ ở đâu? như thế nào? nghi thức ở nhà thờ nước ngoài có khác gì ở Việt Nam không? tham gia sinh hoạt cộng đoàn như thế nào? xưng tội?” v.v không? Chia sẻ với các bạn một chút, một trong những lý do mình chọn đi du học Ireland là bởi vì Ireland là một đất nước có tỷ lệ người theo đạo Công Giáo khá cao (Báo cáo tổng kiểm tra dân số năm 2016 là 78.3%…
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