Wonderful Tech @Taiwan

AppWorks, a venture capital firm based in Taiwan, has invested in several companies during their Series A rounds. Notable investments include: 1. **Carousell** (2018, Series C): A classifieds marketplace for buying and selling items. 2. **Concept Art House** (2021): Specializes in NFTs and video game art creation. 3. **Cyber Sierra** (2021): Offers cyber risk solutions and insurance. 4. **Dapper Labs** (2019): Creator of NBA Topshot and the Flow blockchain. 5. **Dappio** (2022): Aggregates yields across DeFi and NFTs. 6. **Dcard** (2020, Series C): A forum-based social platform. 7. **Deep Sentinel** (2018, Series A): AI-based home protection. 8. **Docosan** (2021, Series Seed): A healthcare marketplace. 9. **Eden Farm** (2021, Series A): A B2B agritech startup. 10. **EMQ** (2017, Series A): A financial technology company focusing on remittances. 11. **Fandora** (2014, Series A): Online seller of illustration merchandise. For more information on AppWorks and their investments, you can v

 Designing an autocomplete feature for a search engine involves understanding user behavior, optimizing for speed and relevance, and ensuring the system can handle a large number of requests. Here's a step-by-step guide on how you might approach this: 1. **Requirement Gathering (需求收集)**    - **User Experience (用戶體驗)**: Understand the latency requirements. Autocomplete suggestions need to be fast, typically returning in under 100 milliseconds.    - **Scale (規模)**: Predict the number of requests per second during peak times. This will help determine infrastructure needs.    - **Relevance (相關性)**: Ensure the suggestions are relevant to the users. 2. **Data Collection (數據收集)**    - Gather a list of commonly searched queries from the search logs.    - Monitor user interactions with the autocomplete feature to refine and improve over time. 3. **Trie Data Structure (Trie數據結構)**    - Use a Trie (or Prefix Tree) which is especially efficient for this use case. As the user types, the system

Designing a video streaming server involves multiple technical aspects and intricate architectural decisions. Here's a high-level consideration and recommended steps from a system design perspective: 1. **Define Requirements (確定需求)**:    - **Throughput (吞吐量)**: How many client connections does your server need to support simultaneously?    - **Latency (延遲)**: How quickly should the streaming begin to play?    - **Video Quality (視頻質量)**: Are you supporting resolutions like 4K, 1080p, 720p, etc.?    - **Streaming Type (串流類型)**: Do you need to support live streaming or VOD (Video on Demand)? 2. **Choose Appropriate Protocols (選擇適當的協議)**:    - **HLS (HTTP Live Streaming)** and **DASH (Dynamic Adaptive Streaming over HTTP)** are popular streaming protocols today. Both support Adaptive Bitrate Streaming (ABR), adjusting video quality dynamically based on a user's network condition.    - **RTMP (Real-Time Messaging Protocol)**: Though less commonly used now, it remains important in ce

### HMD Global and Nokia: Assessing the Past, Present, and Future of Their Partnership Since 2016, Nokia and HMD Global have successfully maintained a collaborative relationship that has revitalized the Nokia brand through a range of mobile and tablet devices. The partnership has been structured around a brand licensing agreement that facilitates the global sale of devices bearing the Nokia brand. But recent developments suggest a potential shift in strategy for HMD Global, raising several questions about the future of the partnership. #### **Historical Background of the Partnership** The collaboration between Nokia and HMD Global blossomed out of a mutual objective to resurrect the once iconic Nokia brand. The agreement was founded on a well-defined business model encompassing brand licensing, shared technologies, and revenue-sharing parameters that aligned with the vision to rejuvenate the Nokia brand while ensuring a strategic business growth. #### **A New Era with HMD’s Own Brand**

### The Revival of Nokia: An Insight into the Nokia-HMD Global Partnership In a dynamic and fiercely competitive mobile device market, alliances and partnerships are not uncommon. One such notable collaboration is between Nokia, a veteran in the telecommunications industry, and HMD Global, a relatively new player aiming to make significant strides in the market. Here we delve deep into the partnership between these two Finnish companies, exploring the synergy that brings Nokia’s legacy into the modern smartphone era. #### **Background** **Nokia**, with its rich history stemming from a paper manufacturing venture to becoming a leader in the telecommunication equipment and mobile communications devices, was a global giant in the mobile manufacturing sector during the early 2000s. However, with the advent of smartphones, Nokia's market share gradually dwindled. **HMD Global**, founded in 2016, came into existence with the primary goal to create and market mobile phones and tablets und

### The Revival of Nokia: An Insight into the Nokia-HMD Global Partnership In a dynamic and fiercely competitive mobile device market, alliances and partnerships are not uncommon. One such notable collaboration is between Nokia, a veteran in the telecommunications industry, and HMD Global, a relatively new player aiming to make significant strides in the market. Here we delve deep into the partnership between these two Finnish companies, exploring the synergy that brings Nokia’s legacy into the modern smartphone era. #### **Background** **Nokia**, with its rich history stemming from a paper manufacturing venture to becoming a leader in the telecommunication equipment and mobile communications devices, was a global giant in the mobile manufacturing sector during the early 2000s. However, with the advent of smartphones, Nokia's market share gradually dwindled. **HMD Global**, founded in 2016, came into existence with the primary goal to create and market mobile phones and tablets und

Kaggle itself provides some great free resources and online courses, which can help you prepare for their contests. Here are a few: 1. **Kaggle Learn**: Kaggle's own "Learn" platform has a number of free, fast-paced courses designed to get you up to speed with the most important tools and techniques used in data science:    - **Python**: Teaches the basics of Python programming and data science.    - **Intro to Machine Learning**: Covers the fundamental concepts required to get started with machine learning.    - **Intermediate Machine Learning**: Introduces more complex machine learning models, including handling missing values and categorical variables, and using pipelines.    - **Data Visualization**: Teaches how to create beautiful and informative visualizations.    - **Pandas**: Introduces the Pandas library, which is fundamental for data analysis and manipulation in Python.    - **Deep Learning**: Covers the basics of deep learning, using the TensorFlow library.    

Yes, Kaggle is a popular platform for data science competitions, but there are several others that you might be interested in as well. Here are a few: 1. **Zindi**: Zindi is a platform for data scientists in Africa to connect and compete. They run competitions (both for profit and non-profit) focused on solving Africa's most pressing problems. 2. **DrivenData**: DrivenData hosts competitions that aim to address some of the world's biggest social challenges. The challenges range from health, education, climate, and more. 3. **CodaLab Competitions**: CodaLab is an open-source web platform that enables researchers, developers, and data scientists to collaborate. They have a section dedicated to competitions. 4. **CrowdANALYTIX**: CrowdANALYTIX hosts data science and AI-related contests and also has an active community of data scientists. 5. **DataScienceGlobal Impact Challenge**: This is an annual competition aimed at data scientists and non-profits. The goal is to showcase how da

Exploratory Data Analysis (EDA) is a critical step in any data science project. It involves understanding the data you're working with, discovering patterns, identifying anomalies, testing hypotheses, and checking assumptions using statistical summaries and graphical representations. Here's a bit more detail: 1. **Understanding the Data**: Start by checking what each column represents, the types of values (categorical, numerical, binary, etc.), and get a general sense of the data structure. 2. **Summary Statistics**: Pandas provides a `describe()` function that gives a useful summary of the numerical columns. It shows the mean, standard deviation, min, max, and quartiles. For non-numeric data, you can use the `value_counts()` method to see the distribution of categories. 3. **Visualizing the Data**: Graphical representations can help you understand the data better. Histograms and box plots are useful for visualizing distributions, scatter plots can show relationships between va

Participating in Kaggle competitions is a great way to learn and apply data science techniques. Here are some steps and tips to get you started: 1. **Create a Kaggle Account**: The first step is to create a Kaggle account, if you haven't already. 2. **Find a Competition**: Browse the Competitions section on Kaggle to find one that interests you. If you're a beginner, you might want to start with one of the "Getting Started" competitions, such as the "Titanic: Machine Learning from Disaster". 3. **Understand the Problem Statement**: Read the competition details carefully to understand the problem you need to solve, the data you have to work with, and the metric on which your solution will be evaluated. 4. **Download the Data**: Download the provided datasets. Kaggle competitions usually provide a training set, which includes the target variable, and a test set, which you'll use to make predictions for submission. 5. **Explore the Data**: Use techniques su

Yes, there are several best practices you can follow when writing code in Jupyter Notebooks for data analysis: 1. **Clear and descriptive naming**: Use clear and descriptive names for variables, functions, and so on. This makes your code easier to understand and maintain.  2. **Commenting and Documentation**: Make sure to document your code well. This includes adding comments to explain complex code blocks, and using docstrings for functions and classes. 3. **Modular and Reusable Code**: Encapsulate code that performs a specific task into a function. This makes your code more readable, reusable, and maintainable. 4. **Minimal use of global variables**: Try to avoid using global variables where possible, and pass variables to your functions instead.  5. **Consistent Coding Style**: Following a consistent coding style can make your code much easier to read and understand. You can follow the PEP 8 -- Style Guide for Python Code. In addition to these, here are some Jupyter Notebook specifi

QIoT Suite 2.0.009 ( 2022/06/09 ) [Enhancements] - Renewed the code signing certificate on the application. QIoT Suite Lite 2.0.008 ( 2021/07/29 ) [Fixed Issues] - Selecting TLS 1.3 for secure connection (HTTPS) in the System Administration page would not allow users to log in to QIoT Suite. - The system would automatically delete the lxdbr0 interface. - Notification Center would not display the QIoT Suite logs. QIoT Suite Lite 2.0.005 ( 2020/12/07 ) [Fixed Issues] - Users would not be able to log in to QIoT Suite using the user account that was created using the same login credentials in both QTS and QIoT Suite application. QIoT Suite Lite 2.0.003 ( 2019/09/09 ) [New Features] - Added support for the OPC UA protocol: - QIoT OPC UA Client: connects to OPC UA servers - QIoT OPC UA Server: communicates with OPC UA clients and transfers data - QIoT OPC UA Gateway: maps data between OPC UA servers and clients - QOPCUA nodes: read, subscribe, and write to specific OPC UA tags in the QIoT ru

Responsible AI, also known as ethical AI or trustworthy AI, refers to the development and deployment of artificial intelligence (AI) systems that prioritize fairness, transparency, accountability, privacy, and social impact. It is an approach that aims to address the potential risks and challenges associated with AI technologies while maximizing their benefits for individuals, organizations, and society as a whole. The rapid advancement of AI technologies has brought about numerous opportunities and benefits across various domains such as healthcare, finance, education, and transportation. However, these advancements also raise concerns about potential biases, discrimination, lack of transparency, and unintended consequences that can arise from AI systems. Responsible AI seeks to mitigate these concerns by integrating ethical considerations into the entire lifecycle of AI development. This involves several key principles and practices: Fairness and Avoidance of Bias: Responsible AI ai

  特別獎  同期統一發票收執聯8位數號碼與特別獎號碼相同者獎金1,000萬元 06634385 特獎  同期統一發票收執聯8位數號碼與特獎號碼相同者獎金200萬元 66882140 頭獎  同期統一發票收執聯8位數號碼與頭獎號碼相同者獎金20萬元 25722152 93412693 16957025 二獎 同期統一發票收執聯末7 位數號碼與頭獎中獎號碼末7 位相同者各得獎金4萬元 三獎 同期統一發票收執聯末6 位數號碼與頭獎中獎號碼末6 位相同者各得獎金1萬元 四獎 同期統一發票收執聯末5 位數號碼與頭獎中獎號碼末5 位相同者各得獎金4千元 五獎 同期統一發票收執聯末4 位數號碼與頭獎中獎號碼末4 位相同者各得獎金1千元 六獎 同期統一發票收執聯末3 位數號碼與 頭獎中獎號碼末3 位相同者各得獎金2百元 1. 領獎期間自112年4月6日起至112年7月5日止 ，中獎人請於領獎期間攜帶國民身分證(非本國國籍人士得以護照、居留證或內政部移民署核發入出境許可證等替代)及中獎統一發票，依代發獎金單位公告之兌獎營業時間臨櫃兌領，逾期不得領獎。  2.統一發票未依規定載明金額者，不得領獎。  3.統一發票買受人為政府機關、公營事業、公立學校、部隊及營業人者，不得領獎。  4.中三獎(含)以上者，依規定應由發獎單位扣繳20﹪所得稅款。  5.中五獎 及雲端發票專屬獎500元（含）以上者，依規定應繳納0.4%印花稅款，但已於財政部電子發票整合服務平台或統一發票兌獎APP設定領獎帳戶兌領獎金者，免繳納印花稅。  6.中獎之統一發票如同時對中多數獎項，以兌領一個獎項為限。  7.詳細領獎規定，請查閱「統一發票給獎辦法」。若有疑義，請洽財金公司客服專線：4128282(手機請撥：02-4128282)，或至財金公司網站查詢。 對發票，推薦使用發票怪獸 嗨嗨～我在用可愛又方便的發票怪獸對獎，在註冊時輸入我的好友邀請碼UU1SJ2TH，一起賺怪獸幣換好禮吧！下載連結： https://friendo.page.link/Z6j33dw2gABBYtHJ7

  Learning Android application development in just 10 days may be challenging, but it's not impossible. Here are some suggestions to help you get started: Understand the basics: Start by understanding the basic concepts of Android development, such as the Android SDK, the development environment, and the application components. Choose a programming language: Android development is primarily done in Java or Kotlin. Choose one of these languages and learn the basics of it if you don't already know them. Learn the Android Studio IDE: Android Studio is the official integrated development environment for Android development. Learn how to use it to create, run, and debug your Android applications. Learn about layouts and views: The user interface (UI) of an Android application is created using layouts and views. Learn about different types of layouts and views, such as LinearLayout, RelativeLayout, and TextView. Work on projects: Start working on small projects, such as creating a si

Developing proficiency in natural language processing (NLP) in just 10 days is a challenging task, but it's not impossible. Here are some suggestions to help you get started: Learn the basics: Start by learning the basic concepts and terminology of NLP, such as tokenization, stemming, lemmatization, part-of-speech tagging, and named entity recognition. You can find plenty of resources online, including tutorials, videos, and textbooks. Choose a programming language: NLP is often implemented using programming languages like Python, Java, or C++. Choose a language you are familiar with or interested in learning. Use NLP libraries: There are many libraries available for NLP, such as NLTK, spaCy, and Stanford CoreNLP. These libraries can help you perform NLP tasks quickly and easily. Practice with datasets: Practice on real-world datasets, such as news articles, reviews, or social media posts, to get familiar with different types of text data. Work on projects: Start working on small