Akita University

Content／学習内容

• Basic of Image Processing

  • Image Compression

  This lecture covers the basics of image processing. It explains analog vs. digital, A/D conversion, resolution, bit depth, pixels, and color spaces. Next, it introduces image compression methods (lossless/lossy) and key formats (BMP, JPEG, PNG, TIFF). Finally, it covers pattern recognition and machine learning, discussing feature extraction, distance calculation, and classification, with examples in character recognition and image classification.

  Videos

  ／学習動画

  • What are Digital and Analog?

    This lecture covers the basics of image processing, including analog vs. digital, A/D conversion, resolution, bits & bytes, pixels, and color spaces (RGB, CMY), explaining the structure of digital images.

  • What is Digital Image?

    This lecture covers image data size, resolution, color depth, compression methods (lossless/lossy), and key formats (BMP, JPEG, PNG, TIFF), emphasizing the importance of efficient digital image processing.

  • Introduction of Pattern Recognition and Machine Learning

    This lecture covers pattern recognition and machine learning, explaining feature extraction, distance calculation, and classification with examples like letters and animals, highlighting the difference from simple search.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Pattern Recognition and Machine Learning

  • Machine learning
  • Neural network

  This lecture covers pattern recognition and machine learning, explaining distance-based classification, supervised vs. unsupervised learning, kNN, neural networks, deep learning, CNNs, transformers, and applications in hyperspectral imaging.

  Videos

  ／学習動画

  • Pattern Recognition

    This lecture introduces pattern recognition basics, classification via distance calculation, and machine learning, highlighting feature extraction and different distance metrics.

  • Machine Learning (1)

    This lecture covers nearest neighbor methods, supervised vs. unsupervised learning, classification vs. regression, and applications of machine learning.

  • Machine Learning (2)

    This lecture explains neural networks, deep learning, CNNs, and transformers, highlighting advances in computing power and development environments that drove their widespread adoption.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Hyperspectral Imaging

  • Feature Extraction
  • Machine Learning

  This lecture covers hyperspectral imaging fundamentals, data processing, and machine learning techniques. It explains differences from RGB, spectral absorption, PCA, K-means, and SVM, with practical Python exercises. Applications include ore grade estimation, mineral identification, and environmental monitoring. The course discusses hyperspectral imaging’s role in assessing and recovering mining-affected areas. Students apply learned techniques through assignments, enhancing practical skills.

  Videos

  ／学習動画

  • Introduction of Hyperspectral Imaging

    This lecture introduces hyperspectral imaging, explaining differences from RGB, spectral features, and applications in mineral exploration and environmental monitoring, emphasizing the importance of light-matter interactions like reflection and absorption in analysis.

  • Getting Ready for Python Programming and Machine Learning

    This lecture introduces Python basics for hyperspectral data analysis, covering light absorption, preprocessing, feature extraction, PCA, K-means, and SVM, along with practical visualization and classification techniques.

  • Machine Learning for Hyperspectral Images

    This lecture reviews hyperspectral image processing, introduces classification and ore grade estimation tasks, discusses applications in mining damage detection and environmental recovery, and explores the use of satellite data.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Python Tutorial; Grammar

  • Programming

  This class provides the fundamental grammatical knowledge of Python, a programming language widely used for deep learning, through exercises.

  Videos

  ／学習動画

  • Python grammar; Data Type

    The data type of variables in Python is explained.

  • Python Grammar; Statements, Functions

    Several flow control statements, “if” statements and “for” statements, and functions are explained.

  • Excercise

    Learn practical programming through exercises

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Python Tutorial: Numpy

  • Numpy

  This class provides instructions on how to use a Python library called “Numpy” to operate arrays.

  Videos

  ／学習動画

  • Array Creation

    Create an array with Numpy.

  • Array Operations

    Operate an array with Numpy

  • Numpy Functions

    Use Numpy functions for array calculations

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Python Tutorial; Matplotlib

  • Matplotlib

  This class provides data visualization techniques with Matplotlib.

  Videos

  ／学習動画

  • Basic Graph Visualization

    Visualize line graph, scatter plot, histogram, and heat map with Matplotlib.

  • Other Graphs

    Visualize other types of graphs

  • Exercise

    Learn Matplotlib through exercise.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Python Tutorial; Pandas

  • Pandas

  This class provides the use of Pandas to analyse table data.

  Videos

  ／学習動画

  • Basic operation of Pandas

    Operate table data with Pandas.

  • Data Analysis with Pandas

    Visualiza the data by calculating statistical metrics with Pandas, and get insight from the data

  • Exercise

    Learn Pandas through Exercise

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Python Tutorial: Scikit-learn

  • Scikit-learn
  • Machine Learning

  This course offers the use of Scikit-learn to develop a machine learning model.

  Videos

  ／学習動画

  • Machine learning model development workflow

    Introduce a common workflow to develop machine learning model

  • Model development with Scikit-learn

    Develop a machine learning model with Scikit-learn

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Machine Learning Hands-on

  • Mining

  This course provides the following content. Basic knowledge of machine learning, how to develop a machine learning model for the mining industry.

  Videos

  ／学習動画

  • Machine Learning and the Mining Industry

    Explain the relationship between Machine learning and the mining indstury.

  • Excercise

    Develop a machine learning model using the minining related dataset.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Gas and Dust Control for Improvement of Underground Work Environment

  • Dust Collector
  • Dust Concentration Measurement

  This lecture explains the importance of dust control in underground work environments and introduces specific countermeasures. It covers the mechanisms and applications of various dust collectors, including gravity, cyclone, filter, wet scrubber, and electrostatic precipitators, and discusses selection methods based on cost and efficiency. The lecture also compares dust concentration measurement methods, such as the sampler method and light scattering method, and introduces personal samplers for monitoring workers’ dust exposure. A quiz is conducted at the end to assess understanding.

  Videos

  ／学習動画

  • Introduction of Gas and Dust Control in Underground Mines

    This lecture explains dust control in underground work environments. It covers the characteristics and applications of various dust collectors, including gravity, cyclone, filter, wet scrubber, and electrostatic precipitators. It also introduces dust concentration measurement methods, such as the sampler method and light scattering method. Finally, a quiz is conducted to reinforce students’ understanding.

  Lecturers

  ／講師

  • Yuichi Sugai

    Professor, Faculty of Engineering Department of Earth Resources Engineering, Kyushu University

• Communication Systems in Underground Mines

  • Wi-Fi Direct
  • Power Line Communication (PLC)

  The lecture provides an overview of communication systems in underground mines. The lecturer first introduces his background and shares insights from his visits to mines in South Africa and other locations. He explains the importance of communication in underground mining and highlights the challenges, such as signal attenuation and the constraints of narrow tunnels. Traditional wired communication and leaky feeder systems are discussed, along with their limitations. He then presents his research on a cost-effective communication system that integrates Wi-Fi Direct and power line communication. The lecture concludes with experimental results and an analysis of its cost-reduction benefits.

  Videos

  ／学習動画

  • Introduction of Communication Systems in Underground Mines

    The lecture introduces communication systems in underground mines. After presenting his background, the lecturer discusses mining site visits, emphasizing the importance and challenges of underground communication. He introduces his research on a cost-effective hybrid communication system using Wi-Fi Direct and power line communication.

  Lecturers

  ／講師

  • Hajime Ikeda

    Associate Professor, Department of Systems, Control and Information Engineering, Asahikawa National College of Technology

• Environmentally Harmonious Mining System Utilizing Knowledge from Inactive and Abandoned Mine Management

  • Digital Twin
  • Environmentally Harmonious Mining

  This lecture introduces “Smart Mining Plus,” an environmentally harmonious mining system using knowledge from Japan’s inactive mine management. AI, digital twins, and multimodal sensing are applied to minimize environmental impact and ensure sustainability. A case study focuses on Kazakhstan’s mines, addressing mine drainage and pollution control. The lecture also explores optimizing mining operations and human resource development to balance resource extraction and decarbonization goals for a sustainable future.

  Videos

  ／学習動画

  • Introduction of SATREPS Project for Kazakhstan

    This lecture introduces “Smart Mining Plus,” an environmentally harmonious mining system utilizing AI and digital twins to reduce environmental impact and ensure sustainable mining using knowledge from Japan’s inactive mine management.

  Lecturers

  ／講師

  • Youhei Kawamura

    Professor, Division of Engineering, Hokkaido University

• Student Presentations (1)

  Student presentations toward assignments

  Videos

  ／学習動画

  • Application of Machine Learning on the Classification of Bushveld Geochemical Data of Chromite Layers in South Africa

    Geochemical data of chromite layers in South Africa’s Bushveld Complex were classified using machine learning. Python and Random Forest were utilized, achieving 69% accuracy. Removing outliers and expanding data are key to improving accuracy.

  • Machine Learning for Geochemical Classification of Chromitite

    Machine learning was applied for geochemical classification of chromitite. After data processing, SVM, decision trees, and Random Forest were compared. Random Forest achieved the highest accuracy (92%), suggesting its potential to enhance geological exploration efficiency.

  • Iron Ore Grade Estimation with Hyperspectral Imaging (HIS)

    Hyperspectral imaging was used to evaluate iron ore grade. K-means and SVM were compared, with SVM achieving high accuracy (98.6%). This method is useful for ore classification and reducing environmental impact, improving exploration and beneficiation processes.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Student Presentations (2)

  Student presentations toward assignments

  Videos

  ／学習動画

  • Assignment 1: Sample Classification, Assignment 2: Iron Ore Grade Estimation

    Iron ore grade estimation and sample classification were conducted using hyperspectral imaging. K-means and SVM were compared, with SVM achieving high accuracy (99.6%). Selecting optimal parameters is crucial for improving accuracy, enhancing ore evaluation efficiency.

  • Using Machine Learning for PPV Estimation with Blasting Data

    Machine learning predicts peak particle velocity (PPV) from blasting data. Stacking regressor performed best (R² = 72.3%), aiding environmental impact assessment and blast planning accuracy.

  Lecturers

  ／講師

  • TORIYA Hisatoshi

    Associate Professor, Graduate School of International Resource Sciences, Akita University

  • OWADA Narihiro

    Graduate School of International Resource Sciences, Akita University

• Natural Resources and International Relations

  • Energy Security
  • Belt and Road Initiative
  • Renewable Energy Transition
  • Resource Dependency Risk

  This lecture, Natural Resources and International Relations, explores resource-related issues in international relations, focusing on geopolitics and energy security. The first session introduced fundamental geopolitical concepts, historical contexts, and theories by Mackinder and Spykman, analyzing the evolution of international relations concerning energy resources. The second session focused on Central Asia’s energy geopolitics, discussing China’s Belt and Road Initiative, resource investments, and regional energy security. Additionally, it examined the growing importance of mineral resources in the renewable energy transition and Japan’s risk of dependency on China for resource procurement.

  Videos

  ／学習動画

  • Natural Resources and International Relations (1)

    In the first lecture of “Natural Resources and International Relations,” the instructor introduces himself and his research areas, followed by an explanation of fundamental concepts in geopolitics and energy security. The lecture covers the historical background of geopolitics, theories by Mackinder and Spykman, and the evolution of international relations concerning energy resources. Additionally, it discusses Japan’s energy security challenges and the geopolitical significance of the Middle East.

  • Natural Resources and International Relations (2)

    The second lecture focuses on energy geopolitics and security in Central Asia. It discusses regional order shifts after the Cold War, the impact of China’s Belt and Road Initiative, and China’s economic and energy investments in Central Asian countries. Additionally, the increasing importance of mineral resources for renewable energy transition and Japan’s risk of dependency on China are examined.

  Lecturers

  ／講師

  • Fumiaki Inagaki

    Professor, Graduate School of International Resource Sciences, AkitaUniversity

Staff／スタッフ

• 
  TORIYA Hisatoshi

  Akita University Graduate School of International Resource Sciences

  Associate Professor
• 
  OWADA Narihiro

  Akita University Graduate School of International Resource Sciences
• 
  Yuichi Sugai

  Kyushu University Faculty of Engineering Department of Earth Resources Engineering

  Professor
• 
  Hajime Ikeda

  Asahikawa National College of Technology Department of Systems, Control and Information Engineering

  Associate Professor
• 
  Youhei Kawamura

  Hokkaido University Division of Engineering

  Professor
• 
  Fumiaki Inagaki

  AkitaUniversity Graduate School of International Resource Sciences

  Professor

Competency／コンピテンシー

Contact／お問合せ先

Akita University, Graduate School of International Resource Sciences, International Strategy Division
kokusaisenryaku@jimu.akita-u.ac.jp

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