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NL2SQL: A Revolutionary Technology for Cybersecurity and Maritime Hacking Defense

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In recent years,  "NL2SQL"  has gained attention as a groundbreaking technology that enhances interaction with databases. NL2SQL stands for  Natural Language to SQL , a  natural language processing (NLP) technique that converts human language into SQL queries . This technology is emerging as a  powerful cybersecurity tool , particularly in  cyber threat detection and maritime hacking defense .   1. Enhancing Cybersecurity Monitoring with NL2SQL NL2SQL streamlines security monitoring and threat detection by enabling intuitive queries in natural language. ๐Ÿ”น Security Operation Centers (SOC) can instantly identify threats with queries like: "Show me all abnormal login attempts in the last 24 hours." ๐Ÿ”น SQL Conversion Example: ๋ณต์‚ฌ ํŽธ์ง‘ SELECT * FROM login_attempts WHERE timestamp >= NOW() - INTERVAL 24 HOUR AND failed_attempts > 5 ORDER BY timestamp DESC ; This allows security teams to detect potential hacking attempts quickly wi...

(Environment) (AWS, Mac) Project Execution and Modeling in an Enterprise Setting

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I have resumed engineering and modeling tasks , which I had temporarily set aside to focus on project management and new business planning . For a project that involves optimizing (tuning) individual models for image and text processing , as well as integrating multiple models —a skill I honed during my Ph.D. program—I now require a complex and well-structured work environment . To ensure optimal efficiency under the given constraints , I plan to set up, refine, and document the work environment for future reference. "If I had eight hours to chop down a tree, I would spend six hours sharpening the axe." – Abraham Lincoln (1861–1865), the 16th President of the United States Review of Work Environment 1. Managing Work on an Unstable Server & Data Backup ✅ Backup & Record Management: Using SFTP to store and synchronize data in a structured manner. ✅ GitHub Usage: Limited to baseline model development and version control for key components. ✅ Code & Data Managem...

๐Ÿšข The Impact of Starlink on Maritime Cybersecurity: A Necessary Investment for the Future

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For decades, maritime vessels operated with limited and slow satellite communications , making them less attractive targets for cyberattacks . However, with the introduction of Starlink , ships now have access to high-speed, low-latency internet , transforming them into fully connected digital platforms . While this advancement brings enormous benefits in operational efficiency, it also exposes vessels to unprecedented cybersecurity risks .  SpaceX Debuts Maritime Offering for Starlink As the shipping industry embraces Starlink-powered connectivity , investing in cybersecurity has become a necessity, not an option . This article explores the growing cyber threats faced by ships due to Starlink and how businesses should strategically invest in security measures to mitigate these risks. ๐ŸŒŠ 1. How Starlink is Changing the Cybersecurity Landscape for Ships Traditionally, ships relied on expensive and slow VSAT (Very Small Aperture Terminal) or Inmarsat satellite connections , which...

"Recommender System" (1) Curriculum

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I would like to organize and document the learning curriculum and key research papers of interest for the Recommender System course that I am taking in the final semester of my Ph.D. program. Goals of this Course Collaborative Filtering (CF) A recommendation approach based on user behavior . Neighborhood-based Collaborative Filtering (CF) A method that recommends items based on similarities between users or items . User-based Collaborative Filtering (User-based CF) Recommends items based on similarities between users . Users with similar preferences or behaviors receive similar recommendations. Item-based Collaborative Filtering (Item-based CF) Recommends items based on similarities between items . Items that have been interacted with in a similar way are recommended together

The Importance of Having Personal Principles in Organizational Life

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 I have come to As the first step, I am recording my personal conclusions on the issues I have contemplated over the past month. [Relational Aspects] I do not strive to become someone else in order to be remembered as a good person in the organization. I am who I am. Work-related matters should be discussed in meetings where all relevant team members (or stakeholders) are present. Even if someone feels uncomfortable or is being held accountable, I will not avoid the situation. Instead, I will share the facts accurately and discuss solutions together to foster future growth and stronger relationships. When I recognize actions that go against basic common sense, I will focus on identifying the fundamental issue rather than getting caught up in others’ emotions. I do not indiscriminately offer consideration, comfort, or reprimands to others. I focus solely on facts and do not convey my emotions in judgment. The driving force of my 30s— “An eye for an eye, a tooth for a tooth” ...

"GNN (Graph Neural Network) ML Learning" (1) Curriculum - Approach

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Shifting Perceptions and Expectations of AI from Companies The way companies perceive and expect from AI is evolving. Until now, aside from cutting-edge research and product development , the role of AI engineers and data scientists in enterprises can generally be categorized as follows: Image Processing : Companies have widely utilized CNN-based models for object recognition and comparison (performance improvement). To overcome data scarcity, techniques like few-shot learning have been applied in areas such as product search, similar image/product recommendation, and design generation . Text Processing : Enterprises have leveraged various Transformer-based models trained on proprietary datasets for customer intent recognition and sentiment analysis . Data-Driven Decision Support : Companies often assume they possess sufficient data, but in many cases, they lack the necessary datasets. AI teams analyze available data, form hypotheses , and generate insightful reports to support an...

(ICML 2019) EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks EfficientNet is a highly influential paper that has gained significant attention in the field of image classification due to its outstanding performance . For projects requiring extensive training time or computational resources , EfficientNet serves as a valuable approach to enhancing ConvNet performance . It provides an efficient and scalable method for training convolutional neural networks while optimizing accuracy and computational cost, making it highly applicable for real-world AI deployment . ๐Ÿ”— Research Paper: EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks ๐Ÿ“Œ Key Resources & Reviews ๐Ÿ“– Paper Review Summaries: Bellzero’s Review Laonple Blog Review ๐Ÿ’ป Source Code (PyTorch Implementation): GitHub: EfficientNet-PyTorch  

(Environment) (Cairo) – (1) Installing Required Libraries to Convert SVG Files to PNG

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Installing Required Libraries to Convert SVG Files to PNG The goal was to apply NBP OCR to SVG images and record the output as JSON (text, coordinates) . To achieve this, the first step was to convert the ".svg" file into ".png" . Initially, I thought that simply installing cairo via pip would suffice, but I soon realized that additional steps were necessary . To avoid wasting time solving issues when I attempted it again later, I decided to document the process and share it . If you need code references or encounter any setup issues, please feel free to leave a message here: https://github.com/shipjobs/HAND2TEXT/issues . Environment Language: Python 3.8.3 64bit Operating System: Windows 10 Development Environment: Visual Studio Code To convert an ".svg" file to ".png" , if you import the libraries as shown below, you will naturally encounter a reference error : import  cairo  from  svglib.svglib  import  svg2rlg  import  cairosvg For those...

(Cloud) NCP > AI Service > OCR review

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CLOVA OCR (optical character reader) Service review ๋ฌธ์„œ๋ฅผ ์ธ์‹ํ•˜๊ณ , ์‚ฌ์šฉ์ž๊ฐ€ ์ง€์ •ํ•œ ์˜์—ญ์˜ ํ…์ŠคํŠธ์™€ ๋ฐ์ดํ„ฐ๋ฅผ ์ •ํ™•ํ•˜๊ฒŒ ์ถ”์ถœ CLOVA OCR (๊ด‘ํ•™๋ฌธ์ž์ธ์‹) ์„ ํ•œ๋ฒˆ ์‚ฌ์šฉํ•ด ๋ณธ๋‹ค๋ฉด, NCP๊ฐ€ ์ œ๊ณต ์ค‘์— ์žˆ๋Š” AI Service ๋“ค ์— ๋Œ€ํ•˜์—ฌ ๋ณด๋‹ค ์‰ฌ์šด ์ ‘๊ทผ์ด ๊ฐ€๋Šฅํ•ด์งˆ ๊ฑฐ๋ผ ์ƒ๊ฐ ํ•˜๊ฒŒ ๋˜์–ด review ๋ฅผ ํ•ด๋ณด๊ณ ์ž ํ•ฉ๋‹ˆ๋‹ค. [์ ‘๊ทผ] Products & service : https://console.ncloud.com/dashboard OCR Service ๊ฒฝ๋กœ : Classic / CLOVA OCR / Domain [์ด์šฉ ๋ฐฉ์‹] ์„œ๋น„์Šค ํƒ€์ž… General / Template / Document ์„ ํƒ์— ๋”ฐ๋ผ Text OCR / ํ…œํ”Œ๋ฆฟ ๋นŒ๋” / Document ๋ฒ„ํŠผ์ด ๋…ธ์ถœ๋˜๋Š” ํ˜•์‹์œผ๋กœ ์„œ๋น„์Šค๋ฅผ ์„ค์ •ํ•จ  Text OCR (ํ…์ŠคํŠธ๋งŒ ์ถ”์ถœ)  ๊ณผ Template ๋นŒ๋” ํ˜•ํƒœ (ํŒ๋… ์˜์—ญ ์ง์ ‘ ์ง€์ •์„ ํ†ตํ•ด ์ธ์‹ ๊ฐ’ ์ถ”์ถœ ํ›„ ํ…Œ์ŠคํŠธ ๋ฐ ๊ฒฐ๊ณผ ์ „์†ก์ด ๊ฐ€๋Šฅ) ๋Š” ์„œ๋น„์Šค ํƒ€์ž…์— ๋”ฐ๋ผ ์•„๋ž˜์˜ 2๊ฐ€์ง€ ๋ฐฉ์‹์ด ์žˆ์œผ๋ฉฐ 1. General OCR : ์šฐ๋ฆฌ๊ฐ€ ์ผ๋ฐ˜์ ์œผ๋กœ ์ƒ๊ฐํ•˜๋Š” png, jpg์ด๋ฏธ์ง€ ํ˜น์€ pdf ์— ์กด์žฌํ•˜๋Š” text ๋“ค์„ ๋ชจ๋‘ ์ฝ์–ด ์˜ค๊ณ ์ž ํ•˜๋Š” ๋ฐฉ์‹ 2. Template OCR : ์šด์ „ ๋ฉดํ—ˆ์ฆ, ์‹ ์šฉ ์นด๋“œ, ์ฃผ๋ฏผ ๋“ฑ๋ก ๋“ฑ๋ณธ ์ด๋ฏธ์ง€ ๋“ฑ ์ด๋ฏธ์ง€๋‚ด ์ •ํ•ด์ง„ ํŠน์ • ์˜์—ญ์„ ๊ธฐ์ค€์œผ๋กœ text ๋“ค์„ ์ฝ์–ด ์˜ค๋Š” ๋ฐฉ์‹ Document ๋ฐฉ์‹์€ ๋จธ์‹ ๋Ÿฌ๋‹ ๊ธฐ๋ฐ˜์œผ๋กœ ๋ฌธ์„œ์˜ ์˜๋ฏธ์  ๊ตฌ์กฐ๋ฅผ ์ดํ•ดํ•˜๋Š” ํŠนํ™” ๋ชจ๋ธ ์—”์ง„์„ ํƒ‘์žฌํ•˜์—ฌ ์ž…๋ ฅ ์ •๋ณด(key-value)๋ฅผ ์ž๋™ ์ถ”์ถœํ•˜๋Š” ๋ฐฉ์‹ ์ธ์‹ ๋ชจ๋ธ๋กœ๋Š” ๋ฏธ๋ฆฌ ์ •ํ•ด์ง„ ์‚ฌ์—…์ž ๋“ฑ๋ก์ฆ, ์‹ ์šฉ์นด๋“œ,์˜์ˆ˜์ฆ, ์‹ ๋ถ„์ฆ, ๋ช…ํ•จ์ด ์ œ๊ณต ๋˜๋ฉฐ ์ด๋ฅผ ์„ ํƒํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. [์ด๋Ÿฌํ•œ Type ๋ณ„ ์„œ๋น„์Šค๋ฅผ ์ด์šฉํ•˜๋Š” ๋ฐฉ๋ฒ• ๋˜ํ•œ 2๊ฐ€์ง€๋กœ ๊ตฌ๋ถ„ ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.] 1. NCP OCR ์‚ฌ์ดํŠธ์— ์ ‘์†ํ•ด์„œ ์ œ๊ณต๋˜๋Š” UI ํ™”๋ฉด์œผ๋กœ ์ ‘๊ทผ ํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์›ํ•˜๋Š” ์ด๋ฏธ์ง€ ํŒŒ์ผ์„ drag and drop์œผ๋กœ ๋“ฑ๋กํ•˜๊ณ  ํ…...