| Program / Major | mDP | Goals | Courses |
|---|---|---|---|
| Fundamental Mechanical Engineering | F | 産業界や社会の要請を把握して解決するべき課題を設定し、さまざまな工学分野の知識を関連付けながら設計生産技術を活用することで、立案した構想に従って研究を進め課題を解決することができる。 | Sub |
| Advanced Mechanical Engineering | F | 産業界や社会の要請を把握して解決するべき課題を設定し、機械工学の学理を応用して異分野を含む融合分野で革新的な機能を創成することができる。 | Sub |
| Environment and Materials Engineering | B | 地球環境や地域社会との調和を見据えて、さまざまな工学分野に関わる問題を解決することができる。 | Sub |
| Chemistry and Biotechnology | B | 地球環境や地域社会との調和を見据えて、さまざまな工学分野に関わる問題を解決することができる。 | Sub |
| Electrical Engineering and Robotics | D | 電気工学や関連する工学の技術分野を課題に適用し、社会の要求を解決するために応用することができる。 | Sub |
| Advanced Electronic Engineering | E | 専門的デザイン課題について解決する能力を身に付けることができる。 | Sub |
| Information and Communications Engineering | F | 社会のニーズに対して技術課題を主体的に発見し、工学分野における分野横断的な知識も活用しつつ、計画的・継続的に取り組んで課題を達成することができる。 | Sub |
| Computer Science and Engineering | G | 技術的課題に対してさまざまな工学分野の知識を関連付けながら主体的に取り組み、継続的に学修する能力を身に付けることができる。 | Sub |
| Urban Infrastructure and Environment | C | 数学や⾃然科学などに関する⼯学基礎知識を修得し、⼟⽊⼯学分野において応⽤・利活⽤できる。 | Main |
| Assignment | 1st examination | 2nd examination | Total. | |
|---|---|---|---|---|
| 1. | 5% | 20% | 0% | 25% |
| 2. | 5% | 20% | 0% | 25% |
| 3. | 5% | 0% | 20% | 25% |
| 4. | 5% | 0% | 20% | 25% |
| Total. | 20% | 40% | 40% | - |
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1. | The Role of probability statistics in engineering - Design and decision making under uncertainty |
Read the syllabus to get an overview of the lecture objectives and lecture content. Purchase a reference book | 120minutes |
| 2. | Analytical Model for Uncertain Phenomena 1 - Normal distribution - Log-normal distribution |
Study normal distribution and lognormal distribution. | 120minutes |
| 3. | Analytical Model for Uncertain Phenomena 2 - Poisson distribution |
Study Poisson distribution. | 120minutes |
| 4. | Statistical inference based on observed data 1 - Role of statistical inference in engineering - Sample mean - Sample variance |
Study statistical inference using observed data. | 120minutes |
| 5. | Statistical inference based on observed data 2 - Reliability test - Reliability Interval |
Study statistical tests and confidence intervals. | 120minutes |
| 6. | Statistical inference based on observed data 3 - chi-square test |
Study the chi-square test. | 120minutes |
| 7. | Mid-term examination | Understand the first half of the lecture contents and prepare for the exam | 240minutes |
| 8. | Basics of matrices - Matrix and vector arithmetic - Four arithmetic operations on matrices, transposed matrices, and inverse matrices - Matrix representation and solution of simultaneous equations (both in Excel (using inverse matrix) and by hand (sweep method)) |
Students who have difficulty with matrices should review the basics. | 120minutes |
| 9. | Regression and correlation analysis - Estimation of regression equations by the least squares method - Correlation coefficient |
Understand regression equations using the least-squares method. | 120minutes |
| 10. | Eigenvalue problems 1 - Matrix formulas - Eigenvalue problem |
Review determinants. | 120minutes |
| 11. | Eigenvalue problems 2 - Application of eigenvalue problems |
Review and deepen understanding of eigenvalue problems. | 120minutes |
| 12. | Applications of matrices 1 - Image processing for photogrammetry and remote sensing - Rotation and translation matrices, affine transforms |
Review matrices used in image processing. | 120minutes |
| 13. | Applications of matrices 2 - Projective transformation, Adamar product |
Review the concept of projective transformations and Adamar products | 120minutes |
| 14. | Final examination | Understand the second half of the lecture contents and prepare for the exam | 240minutes |
| Total. | - | - | 1920minutes |
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| N/A | N/A |