电子与技术硕士

Digital Communications

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of digital communication and skills/competencies in the design and performance analysis of the major parts of a modern digital communication systems. The course covers the design and performance analysis of the major parts of a modern digital communication system. It also discusses some fundamental limits for transmission of digital information over noisy channels.

What you will learn

Analyze complex modern digital communication systems.
Identify and summarize common problems in existing digital communication setups.
Propose and formulate solutions for common problems related modulation and noise in digital communication systems.
Evaluate and assess the performance of proposed solutions related to modulation and noise in digital communication systems.

Meet your instructor

Michalis Michaelides

Course content

Session 1: Digital modulation schemes (Part 1)
Session 2: Digital modulation schemes (Part 2)
Session 3: Performance analysis of digital communication systems in the presence of noise (Part 1)
Session 4: Performance analysis of digital communication systems in the presence of noise (Part 2)
Session 5: Optimum signal detection methods
Session 6: Optimum receivers for AWGN channels
Session 7: Source encoding and channel capacity, and error correcting codes.
Session 8: Practical examples and real-life problems.

Teaching methodology

Lectures, group discussion for problem solving, seminars.

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final written exam (60%) Will include combination of numerical exercises and open-ended theoretical questions.

Advanced Digital Signal Processing I

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge on the most important theoretical and practical aspects of advanced digital signal processingand skills/competencies in process analysis of discrete-time signals. The most important knowledge will be developed throughout the course is the analysis of signals and systems with the help of discrete-time Fourier series and transform, and extraction of quantitative parameters for the evaluation of their properties. Significant knowledge is gained about the Discrete Fourier transform and its various applications such as the analysis of design of digital filters of finite and infinite (FIR and IIR) impulse response. With this knowledge, students will be able to address real world problems and design digital filters that are widely used in applications. This course covers theoretical knowledge and applications in the form of computer projects in MATLAB or similar environment.

What you will learn

Analyze discrete-time signals and systems.
Extract quantitative parameters to identify signal properties
Design digital filters of finite and infinite (FIR and IIR) impulse response.
Analyze practical systems from various industrial sectors

Meet your instructor

Takis Kasparis

Course content

Session 1: Fourier series of discrete time signals
Session 2: Discrete Fourier Transform and applications
Session 3: Design of digital filters of finite impact response (FIR)
Session 4: Design of digital filters of infinite impact response (IIR)
Session 5: Design of filters meeting given specifications
Session 6: Analysis and design in practical systems
Session 7: Programming applications in MATLAB environment (Part 1)
Session 8: Programming applications in MATLAB environment (Part 2)

Teaching methodology

Presentations, group discussions, and case studies.

Assessment

Midterm exam (25%) Will include combination of numerical exercises and open-ended theoretical questions.
Computer Projects (35%)
Numerical and theoretical exercises (10%).
Final written exam (30%) Will include combination of numerical exercises and open-ended theoretical questions.

College English

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of the college English is to expand the international cultural vision of students, enhance the daily and academic communication skills of cross-cultural, and enable students to master the language tool of English to promote the study of graduate students more conveniently. The course covers the daily and academic communication in English, academic English writing and speech.

What you will learn

Develop an international cultural vision and the literacy for intercultural communication.
Develop comprehensive English application ability, so that they can use the professional dictionary to read English literature, read English academic papers.
Write a variety of practical styles and academic papers in English, help students master the norms, language and format of practical style writing; master the normative and accurate language of academic paper writing; familiar with the mode of international academic English writing; Cultivate internationally universal academic ethics.
Develop the ability to communicate more smoothly with others in English. Students will be able to attend international conferences, publish academic opinions, public speaking and other communication and communication skills will be further improved

Meet your instructor

XiaoqinZhou

Course content

Session 1 the pronunciation of all vowels and consonant phonetic symbols.
Session 2 learn to spell words and sentences correctly; review the use of basic tenses in English and their application in spoken English.
Session 3 the Academic English Lecture 1: “Identifying key issues.” Understand the importance of academic speech; how to evaluate a good academic speech; the difference between daily conversation and speech; stage phobia.
Session 4 Academic English Lecture 2: “Planning a Presentation”. Explain the eight steps of academic presentation preparation, focus on explaining and practicing the determination of the speech objectives; how to study the audience; how to focus on selected topics and live demonstrations.
Session 5 Academic English Lecture Unit 3: Outlining a Presentation. Learn the importance and significance of the speech outline; learn how to write an outline of the speech.
Session 6 Academic English Lecture Unit 4: “Structuring a Presentation”. Learn to write a speech. How to construct the introductory part of the speech; how to construct the main part of the speech; how to end and invite questions and answer questions. Class practice topic: A virtue in my friend.
Session 7 The Academic English Speech 5: “Using Effective Visual Aides”. Learn the use and production of various visual aids in academic presentations. Classroom Exercise Topic: Read “The Year of Twenty Years Is No Longer” and discuss the topic.
Session 8 Academic English Lecture Unit 6, “Using Nonverbal Languages.” Understand the importance and significance of body language in speech. Learn the expression of the proper body language. Practice exercises and discuss topics: revolution and youth.
Session 9 Academic English writing. The structure and linguistic features of academic papers.
Session 10 Academic English writing. Abstract, key words and document formats of academic papers, lectures and tutorials.
Session 11 Academic English writing. Choosing a topic, learning the difference between a persuasive and expository research paper.
Session 12 Academic English writing. The syllabus and argument structure of the academic papers are explained and counseled, outlining and the structure of paper.
Session 13 Academic English writing. Help students to write the first draft of a paper

Teaching methodology

Lectures, group discussion for problem solving, collaborative learning

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final written exam (60%) Will include combination of numerical exercises and open-ended theoretical questions.

Research on Theory and Practice of Socialism with Chinese Characteristics

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of the major theoretical and practical issues of socialism with Chinese characteristics. The course covers the discussion of the latest achievements of the localization of Marxism. It also discusses the principles and measures to strengthen and innovate social governance.

What you will learn

Identify themes and basic issues of contemporary China
Summarize the major theoretical and practical issues of socialism with Chinese characteristics
Master the main content of the theoretical system of socialism with Chinese characteristics
Analyze and solve practical problems by using this theory
Identify and summarize common problems in society

Meet your instructor

GuibaoLu

Course content

Session 1: the creation and development of socialism with Chinese characteristics
Session 2: the connotation and significance of the new era
Session 3: The Transformation of the Main Contradictions in Chinese Society
Session 4: Socialist economic theory and system with Chinese characteristics
Session 5: the construction of a modern economic system
Session 6: Improve the socialist market economic system
Session 7: A new pattern of comprehensive opening up
Session 8: The political theory and system of socialism with Chinese characteristics
Session 9: The theory and system of socialist culture with Chinese characteristics
Session 10: The strategic position and fundamental task of inheriting and promoting the excellent traditional Chinese culture
Session 11: Guarantee and improve people’s livelihood during development
Session 12: Principles and Measures of Social Governance
Session 13: The significance and connotation of the concept of national security

Teaching methodology

Lectures, group discussion

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final examination （60%） Will include combination of numerical exercises and open-ended theoretical questions.

Matrix Theory

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to learn and master the basic theory and method of Matrix theory. The course covers linear space and linear transformation, Euclidean space and unitary space, as well as the linear transformation on this space, and profoundly reveals the essence and thought of linear transformation on finite dimensional space.

What you will learn

Summarize the concepts related to linear space, master the linear transformation and its matrix representation, and master the concepts related to Euclidean space.

Master the concept of vector norm and matrix norm and their calculation.
Master the concept of matrix series and matrix series, be able to find the limit of matrix series and determine the convergence of matrix power series; master the representation of matrix function and its corresponding calculation method.
Master the triangular decomposition, QR decomposition, full rank decomposition and singular value decomposition of matrices.
Formulate the estimation of eigenvalue bounds, master Gerschgorin’s disc theorem and its extensions, and understand the generalized eigenvalue problem.
Master the concept and computation of generalized inverse matrices and be able to use this concept for theoretical analysis of solutions of systems of linear equations.

Meet your instructor

Tieming Xiang

Course content

Session 1: Linear space and linear transformation （part 1）
Session 2: Linear space and linear transformation （part 2）
Session 3: vector norm and the matrix norm
Session 4: the common norm compatibility
Session 5: Matrix analysis （part 1）
Session 6: Matrix analysis（part 2）
Session 7: The linear constant function differential equation
Session 8: Four matrix decomposition method
Session 9: The characteristic value estimation and Gail round
Session 10: The linear constant function differential equation
Session 11: Matrix decomposition
Session 12: Eigenvalue estimation
Session 13: Generalized inverse matrix

Teaching methodology

Lectures, group discussion and problem solving

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final written exam (60%) Will include combination of numerical exercises and open-ended

Embedded Systems and Applications

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of embedded operating systems and Linux programming. The course covers beginner and intermediate Linux programming and comprehensive examples.

What you will learn

Analyze Linux software implementation in complex embedded systems
Summarize the Linux application tips and tricks
Propose and formulate solutions for a Linux software programming solution for embedded applications
Evaluate the general performance of embedded software

Meet your instructor

Jiadong Cui

Course content

Session 1: Linux basics (part 1)
Session 2: Linux basics (part 2)
Session 3: Linux development environment
Session 4: Linux program design preliminary
Session 5: File I/O
Session 6: File attributes
Session 7: Directory file Management
Session 8: Process control
Session 9: thread
Session 10: Signals and pipe
Session 11: Interprocess communication
Session 12: Network programming
Session 13: Integrated case

Teaching methodology

Lectures, group discussion, programming practice and problem solving

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final exam (60%) A closed - book examination with questions including fill-in-the-blank, short answer and programming methods.

Thesis project (I)

Sun, 01 Jan 2023 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

Petros Aristidou

Course content

Teaching methodology

Assessment

Thesis project (I)

Sun, 01 Jan 2023 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

Petros Aristidou

Course content

Teaching methodology

Assessment

Advanced System Theory and Automatic Control

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge on non-linear systems and control and skills/competencies in complex system control design. The course covers the technological field of non-linear control systems theory, covering modeling approaches, stability analysis, and control design.

What you will learn

Analyze non-linear systems and assess their stability.
Design control solutions for common non-linear systems.
Evaluate the performance of various non-linear control design methods.
Validate practical solutions to control of non-linear problems in industry.

Meet your instructor

Petros Aristidou

Course content

Session 1: Review of linear systems and control
Session 2: Introduction to non-linear systems
Session 3: Introduction to non-linear control systems
Session 4: Performing stability analysis of non-linear systems using a variety of methodologies (Lyapunov stability, passivity, input-output stability etc.) (Part 1)
Session 5: Performing stability analysis of non-linear systems using a variety of methodologies (Lyapunov stability, passivity, input-output stability etc.) (Part 2)
Session 6: Performing stability analysis of non-linear systems using a variety of methodologies (Lyapunov stability, passivity, input-output stability etc.) (Part 3)
Session 7: Design control mechanisms for non-linear systems
Session 8: Practical applications of non-linear control.

Teaching methodology

Presentations, group discussions, case studies.

Assessment

Midterm exam (30%) Will include combination of numerical exercises and open-ended theoretical questions.
Project (20%) Group project assigned to the students during the semester.
Final written exam (50%) Will include combination of numerical exercises and open-ended theoretical questions/

Research Methods

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The purpose of this course is to teach students how to perform their research properly, how to find information on scientific articles from the university’s library, how to write an excellent scientific article for a conference or scientific journal and to help them present the results of their research.

What you will learn

Acquire basic knowledge of how to find information from the library and international databases,
Write successful scientific articles for scientific conferences and journals and excellent research proposals,
Write very good scientific theses,
Analyze and study a subject in depth and write a literature review on the subject,
Acquire the knowledge on how to collect and process data.

Meet your instructor

Petros Aristidou

Course content

Unit 1 Research Basics Chapter 1 Introduction Chapter 2 Empirical Methodology for Conducting Research Chapter 3 Formal Methodology for Conducting Research Chapter 4 Research Supervision
Unit 2 Library Tools and Literature Search Chapter 1 Library Tools Chapter 2 Library Search Chapter 3 Database Search Tips Chapter 4 Digital Libraries
Unit 3 Literature Review Chapter 1 Types of Scientific Literature Chapter 2 Analyzing a Scientific Paper Chapter 3 Writing a Paper Review Chapter 4 Systematic Literature Reviews
Unit 4 Data Chapter 1 The Nature of Data Chapter 2 Collecting Primary Data Chapter 3 Collecting and Analyzing Secondary Data Chapter 4 Quantitative Data Analysis Chapter 5 Qualitative Data Analysis
Unit 5 Writing Up your Work Chapter 1 Writing a Scientific Research Paper Chapter 2 Writing a Thesis

Teaching methodology

Lectures, group discussion, independent research, collaborative discussion.

Assessment

Presentation of thesis topic (20%) Student needs to present their thesis topic in front of an audience.
Written literature review report (50%) Student needs to write a literature review on a selected topic.
Presentation of literature report (30%) Student needs to present their literature review in front of an audience.

Medical Imaging

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge on various medical imaging methods and skills/competencies in design and analysis of medical imaging solutions. This course aims to describe the most important theoretical and practical parameters of the various imaging methods. The course examines the physical principles of the main types of medical imaging such as ultrasound, magnetic resonance imaging, X-rays, CT, SPECT, PET, optical coherence tomography (OCT), and electrical impedance tomography (EIT). The most important knowledge that will be developed through the course is the elaboration and understanding, separation and use of the above concepts. With this knowledge, students will be able to provide solutions to medical imaging problems as well as analyze the data that emerge from them.

What you will learn

Differentiate, classify and compare medical imaging such as ultrasound, magnetic resonance imaging, X-rays, CT, SPECT, and PET.
Analyze applications of the above imaging systems.
Critically distinguish the difference of the above imaging modalities using quantitative comparison factors.
Identify and recommend important requirements for the approval of medical devices

Meet your instructor

Christakis Damianou

Course content

Session 1-2: Physical principles of the main types of medical imaging such as ultrasound, magnetic resonance imaging, X-rays, CT, SPECT, PET, optical coherence tomography (OCT), and electrical impedance tomography (EIT).
Session 3-4: Ultrasound will focus on topics such as waves (transverselongitudinal), ultrasound speed calculation, wavelength, A-Mode, B-Mode, M-Mode, acoustic impedance, reflection, refraction, scattering, attenuation, absorption, transducer design, ultrasound technical errors, ultrasonic doppler, calculation of intensity mechanical and thermal index, ultrasonic components (linear-phase etc.), distinctive ability (axial / lateral), ultrasound imaging phantoms for diagnostic ultrasound, and ultrasound wave equations.
Session 5-6: In magnetic resonance imaging, emphasis will be given to issues such as magnetization creation, Larmor equation, tuning, magnetic resonance imaging, T1 and T2 relaxation, Hardware, Fast spin Echo, Frequency and phase coding, 2-dimensional display, slice selection, Kspace, fast sequences, fMRI and the physical properties of various specialized sequences.
Session 7: X-rays, X-ray tube construction, X-ray interaction with tissues, Xray spectrum, Fluoroscopy, Digital subtraction angiography, Mammography, Osteoporosis Measurement (DEXA method), Dental applications, Linear accelerators, SPECT (γ camera), PET (Cyclotron), Approval of medical devices (CE, FDA), Application for clinical trials.
Session 8: Finally, optical coherence tomography (OCT) and electrical impedance tomography (EIT) will be reviewed.

Teaching methodology

Presentations, group discussion, and laboratory demonstrations.

Assessment

Midterm exam (30%) Will include combination of numerical exercises and open-ended theoretical questions.
Exercises (20%) Written assignements throughout the course.
Final written exam (50%) Will include combination of numerical exercises and open-ended theoretical questions.

Advanced Digital Signal Processing II

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of more advanced digital signal processing methodologies and skills/competencies in analysis of practical problems. The course teaches the theoretical background of digital signal processing methodologies verified by series of computer projects and applications of real problems.

What you will learn

Multirate digital signal processing applications in various practical applications and least-square methods for designing a variety of systems.
Develop solutions for practical problems with a combination of advanced signal processing methodologies.
Evaluate the performance of system modeling and estimation/prediction methods in modern applications

Meet your instructor

Takis Kasparis

Course content

Session 1: Multirate digital signal processing and applications
Session 2: Least-square methods for system modeling and filter design
Session 3: Forward and backward linear prediction
Session 4: AR, MA and ARMA modeling
Session 5: Inverse systems and deconvolution
Session 6: Weiner filters
Session 7: Power spectrum estimation.
Session 8: Introduction to adaptive filters

Teaching methodology

Presentations, group discussions, case studies.

Assessment

Midterm exam (25%) Will include combination of numerical exercises and open-ended theoretical questions.
Computer Projects (35%)
Numerical and theoretical exercises (10%).
Final written exam (30%) Will include combination of numerical exercises and open-ended theoretical questions

Introduction to Photonics

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge on photonics and skills/competencies in the design and performance analysis of communication systems based on photonics. The course will first provide an introduction to photonics and optical communication followed by the analysis of different communication technologies and their practical applications.

What you will learn

Differentiate, categorize, and compare different photonics and optical communication technologies.
Identify the characteristics of optical devices and specify their functionalities.
Propose communication solutions based on photonics technologies.
Evaluate and compare the performance of practical optical communication solutions.

Meet your instructor

Kyriacos Kalli

Course content

Session 1: Introduction to Photonics and Optical Communication Overview of photonics and the applications in different areas such as information technology and communications, healthcare, life sciences, optical sensing, lighting, energy and manufacturing. The evolution of light-wave systems will be discussed before the basics of optical communications systems will be introduced. Session 2: Nature of light and the production of EM radiation for photonics applications i) Wave Nature of Light Light waves in homogeneous media. Refractive index. Group velocity and group index. Magnetic field, Irradiance and Poynting vector. Snell’s law and total internal reflection. Fresnel’s equations. Multiple interference and optical resonators. Temporal and spatial coherence. Diffraction principles. Polarisation. Methods to define the characteristics of light mathematically (Stokes parameters, Jones vectors & matrices) and how to determine these characteristics. ii) Optical sources and transmitters Principles of light emission and amplification in semiconductors, light emitting diodes, semiconductor lasers (edge emitting lasers and VCSELs). Semiconductor science and light emitting diodes (LED). Semiconductor concepts and energy bands. Direct and indirect band-gap semiconductors: E-k diagrams. Pn junction principles and band diagram. LED and materials. Heterojunction high intensity LED and characteristics. Steady state semiconductor rate equation. LED for Optical fibre communications. Single frequency solid state lasers. Quantum well devices. Optical amplifiers. Session 3: Optical waveguides The propagation of light in optical waveguides.Dielectric waveguides and optical fibres. Symmetric planar dielectric slab waveguide. Modal and waveguide dispersion in the planar waveguide. Step index fibre. Numerical aperture. Dispersion in single mode fibres. Bit-rate, dispersion and optical non-linearities, Electrical and optical bandwidth. Graded index optical fibre. Attenuation in optical fibres-light absorption and scattering. Fibre manufacture. Session 4: Optical detectors and receivers The detection of light and the demodulation of light including photoconductors, photodiodes and receiver systems. Principle of the p-n junction photodiode. External photocurrent. Absorption coefficient and photodiode materials. Quantum efficiency and responsivity. The pin, avalanche and heterojunction photodiodes. Phototransistors. Photoconductive detectors and photoconductive gain. Noise in photodetectors. Generic system issues: sources of noise and signal-to-noise ratio, limitations on temporal response and effective bandwidth. Sesison 5-6: Imparting information onto EM radiation & communication techniques i) Basic modulation principles Polarisation and modulation of light. Light propagation in anisotropic media: birefringence. Birefringent optical devices. Optical activity and circular birefringence. Electro-optic effects. Integrated optical modulators. Acousto-optic modulator. Magneto-optic effects. Non-linear optics and second harmonic generation. ii) Modulation Acousto-optic and electro-optic techniques, LED switching, analogue and digital techniques using lasers, AM, FM, phase modulation techniques Session 7-8: Applications for light-wave systems A summary of important concepts of digital communication including base band and broadband digital transmission, bit error rate, bit group error rate and time division multiplexing (TDM) and wavelength division multiplexing (WDM). Trends and new directions in photonic applications i) Noise and detection Noise arising from the properties of fibres, transmitters, receivers and amplifiers as well as the determination of the bit error rate. ii) Optical MUX and DEMUX The operating principle of multiplexers and demultiplexers. Different optical devices, essential to optical networks, optical amplifiers, polarisation control devices, optical isolators, optical filters and diffraction gratings, modulators and switches. iii) Optical systems design Design process for a point-to-point optical links.

Teaching methodology

Lectures, group discussion, independent learning.

Assessment

Midterm exam (30%) Will include combination of numerical exercises and open-ended theoretical questions.
Exercises (20%) Written assignements throughout the course.
Final written exam (50%) Will include combination of numerical exercises and open-ended theoretical questions.

Wireless Communications

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge on wireless communication systems and skills/competencies in the design and performance analysis of wireless communication systems. The course will cover a wide range of subjects including the basic principles, design and performance analysis of cellular systems, the modeling of radio propagation in the wireless channel and multiple access techniques (FDMA, TDMA, CDMA).

What you will learn

Differentiate, categorize, and compare different wireless communication technologies.
Identify the characteristics of wireless devices and specify their functionalities.
Propose communication solutions based on wireless technologies.
Evaluate and compare the performance of practical wireless communication solutions.

Meet your instructor

Michalis Michaelides

Course content

Session 1: Introduction in the technological field of wireless communications.
Session 2: Basic principles, design and performance analysis of cellular systems
Session 3-4: Modeling of radio propagation in the wireless channel
Sessions 5-6: Multiple access techniques (FDMA, TDMA, CDMA)
Session 7: Outlook on future technologies
Sesison 8: Practical applications and code development.

Teaching methodology

Lectures, group discussion and problem solving, and project-based learning

Assessment

Midterm exam (30%) Will include combination of numerical exercises and open-ended theoretical questions.
Project (20%) Group project assigned to the students during the semester.
Final written exam (50%) Will include combination of numerical exercises and open-ended theoretical questions.

Practical scuentific and research training (I)

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

Petros Aristidou

Course content

Teaching methodology

Assessment

Practical scuentific and research training (II)

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

Petros Aristidou

Course content

Teaching methodology

Assessment

Mathematical Methods

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of complex value functions, Fourier transform, Laplace transform, the founder and solution of mathematical and physics equations.The course covers the analysis of complex value functions, calculating some complex integrals with residues, character of special functions, for example, Bessel function, associate Legendre function, and the special Bessel functions. It also discussed the some solution of partial differential equations.

What you will learn

Meet your instructor

Youlin Geng

Course content

Session 1：Complex number and complex variable function (Part 1)
Session 2：Scalar fields and multivalued functions (Part 2)
Session 3：Integral of complex functions
Session 4：Power series expansion of complex functions
Session 5：Computer of residue series
Session 6: Fourier Transform
Session 7: Laplace Transform
Session 8: Founder of Mathematical and Physics Equation
Session 9: The solution of separated variable method to the Mathematical and Physics Equation
Session 10：Series solution of second order ordinary differential equation, eigenvalue problem
Session 11：Spherical functions
Session 12：Cylinder functions
Session 13：Green functions method
Session 14：Integral transformation

Teaching methodology

Lectures, group discussion for problem solving, project-based learning

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final written exam (60%) Will include combination of numerical exercises and theoretical questions

Analog IC Design

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to Using the theoretical knowledge to complete basic unit circuit design. The course covers Analog integrated circuit design basic knowledge and Provide basic theoretical simulation, analog hybrid. Using the theoretical knowledge to complete basic unit circuit design.

What you will learn

Analyze the basic principle of integrated circuit components structure
Analyze basic unit circuit with the theoretical knowledge
Identify and summarize common problems in the integrated circuit process technology
Explain the basics theory of analog circuit devices

Meet your instructor

Xiaofei Kuang

Course content

Session 1: Introduction to Microelectronics
Session 2: Physics of MOS Transistors
Session 3: Pn section, transistor, MOS tube
Session 4: CMOS amplifiers
Session 5: Differential Amplifiers
Session 6: Cascode Differential
Session 7: Common-mode Rejection
Session 8: Differential Pair with Active Load
Session 9: Frequency Response
Session 10: Frequency Response of CS stages
Session 11: Frequency Response of CG stages
Session 12: Frequency Response of Followers
Session 13: Feedback Topologies

Teaching methodology

Presentation, group discussion, and case study.

Assessment

Midterm exam (40%) Will include combination of numerical exercises and open-ended theoretical questions.
Final written exam (60%) Will include combination of numerical exercises and open-ended theoretical questions.

Semiconductor Physics and Devices

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to enable students to master the basic theory of semiconductor physics and main properties of semiconductor, and to lay a necessary professional foundation for the development and design of semiconductor devices and electronic systems and related scientific research work. The course covers crystal structure, carrier modeling, carrier action, pn Junction electrostatics, I-V Characteristics of pn junction diode, optoelectronic diodes, BJT fundamentals, MS Contacts and Schottky diodes.

What you will learn

Analyze the physical mechanism of silicon and other semiconductors
Identify and summarize the main factors affecting device characteristics and common non-ideal effects in transistors
Propose and formulate solutions for common problems of semiconductor devices including modulation and improvement of performance
Assess proposed solutions related to semiconductor devices including modulation and improvement of performance

Meet your instructor

Zhangting Wu

Course content

Session 1: A General introduction of Semiconductors
Session 2: Carrier Modeling (part 1)
Session 3: Carrier Modeling (part 2)
Session 4: Carrier Action (part 1)
Session 5: Carrier Action (part 2)
Session 6: pn Junction Electrostatics
Session 7: pn Junction Diode: I—V Characteristics (part 1)
Session 8: pn Junction Diode: I—V Characteristics (part 2)
Session 9: Optoelectronic Diodes (part 1)
Session 10: Optoelectronic Diodes (part 2)
Session 11: BJT Fundamentals
Session 12: MS Contacts and Schottky Diodes
Session 13: MOS Fundamentals

Teaching methodology

Lectures, group discussion for problem solving, collaborative learning, independent learning

Assessment

Class Performance (40%) Will include homework and discussion
Final written exam (60%) Will include Short Answers and Calculations

VLSI Design

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to help the graduate students to obtain the basic theory and methodology of CMOS digital integrated circuit design. The course covers the basic theory and design method of CMOS device, logic gate, combinational logic, sequential machine and digital system. The course also introduces the design flow of VLSI from RTL to GDSII.

What you will learn

Analyze and design of logic gate, combinational logic, sequential machine and simple digital system
Analyze and design the structure of complex digital system
Master the design flow of VLSI from RTL to GDSII
Experiment the system design or RTL design of a digital chip

Meet your instructor

Qi Ma

Course content

Session 1: Introduction
Session 2: CMOS process technologies and device characteristics
Session 3: Logic gate
Session 4: Combinational logic network
Session 5: Sequential machine
Session 6: Digital system
Session 7: Introduction to VLSI design flow
Session 8: System design (Part 1)
Session 9: System design (Part 2)
Session 10: RTL design (Part 2)
Session 11: RTL design (Part 2)
Session 12: Logic design and Layout design
Session 13: SoC design methodology based on IP.

Teaching methodology

Lectures, discussing, and independent learning

Assessment

Assignments (30%) Written assignments throughout the course.
Final examination （70%） Will include combination of numerical exercises and open-ended theoretical questions.

RF IC Design

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is foster and promote knowledge of RF/microwave integrated circuits and systems. The course covers the design and performance analysis of common methods microwave/RF integrated circuits and systems.

What you will learn

Analyze complex modern RF/microwave integrated circuits systems
Understand and use the basic concepts of RF/microwave integrated circuits and systems
Propose and formulate solutions for microwave/RF integrated circuits.
Identify the unit modules in the RF front-end circuit
Arrange common EDA tools to design circuits

Meet your instructor

LinglingSUN

Course content

Session 1: the basics of RFIC
Session 2: Introduction of wireless transceiver
Session 3: analysis and design of LNA (part 1)
Session 4: analysis and design of LNA (part 2)
Session 5: analysis and design of PA (part 1)
Session 6: analysis and design of PA (part 2)
Session 7: VCO design and phase noise analysis (part 1)
Session 8: VCO design and phase noise analysis (part 2)
Session 9: PLL analysis and design (part 1)
Session 10: PLL analysis and design (part 2)
Session 11: analysis and design of mixer
Session 12: the measurement of RFIC
Session 13: Practical examples

Teaching methodology

Lectures, group discussion for problem solving, collaborative learning

Assessment

Assignments (30%) Written assignements throughout the course.
final exam (70%) Will include combination of numerical exercises and open-ended theoretical questions

Electronic System Design

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to understand and master the general methods and skills of electronic system design. The course covers systematic to study of integrated operational amplifiers, power semiconductor devices, new semiconductor sensors, new integrated circuits, data communication technology, power system design, filter design, Multisim circuit simulation technology, electronic system design example analysis.

What you will learn

Master the ability of comprehensive design of general electronic system.
Analyze of relevant cases of integrated circuits and semiconductors,
Understand the application of integrated circuits and semiconductors in automotive electronics and industrial automation control system,
Identify and summarize common problems in electronic system design.
Evaluate and assess the performance of proposed solutions related to electronic system.

Meet your instructor

Mingyu Gao

Course content

Session 1: Operational amplifiers
Session 2: Amplification circuit design (part 1)
Session 3: Amplification circuit design (part 2)
Session 4: Power semiconductor devices
Session 5: Power system design
Session 6: Semiconductor sensor and filter design
Session 7: MCU / ARM (part 1)
Session 8: MCU / ARM (part 2)
Session 9: A / D and D / A conversion circuit design (part 1)
Session 10: A / D and D / A conversion circuit design (part 2)
Session 11: Communication circuit design
Session 12: Circuit simulation technologies based on Multisim
Session 13: Examples of integrated electronic system design.

Teaching methodology

Lectures, group discussion for problem solving, collaborative learning, independent learning

Assessment

Assignments (40%) Written assignements throughout the course.
Final examination （60%） Will include combination of numerical exercises and open-ended theoretical questions.

Analogue and Mixed IC Design

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to establish a theoretical foundation and gradually master the methodology of analog and mixed IC design for students. The course covers the basic knowledge of analog integrated circuit design and the course design. The first aspect is the basis theory of electric circuit, including the background and development of analog and mixed-signal integrated circuit, CMOS integrated circuit technology and active device, single stage amplifier, differential amplifier, current mirror, active load and voltage reference circuit, output stage, operational amplifier. The other aspect is the course design, including designing and simulating a module of integrated circuit according to circuit requirements

What you will learn

Analyze complex analog and mixed-signal integrated circuit
Design integrated circuit according to circuit requirements
Master expertly the use of EDA software to simulate integrated circuits
Evaluate and assess the performance of analog and mixed-signal integrated circuit

Meet your instructor

Hui Hong

Course content

Session 1: Background and design process
Session 2: CMOS technology
Session 3: Single transistor amplifier
Session 4: Differential amplifier
Session 5: Current sink and current mirror
Session 6: Voltage and current reference
Session 7: Output stage
Session 8: CMOS amplifier design
Session 9: Frequency Response of Amplifiers
Session 10: Op-Amps characteristics and frequency compensation
Session 11: Course design
Session 12: Course design
Session 13: Course design

Teaching methodology

Presentations, group discussions, case studies.

Assessment

In-class assessment (30%) Will include combination of regular discussions, classroom questioning, etc.
Design project (70%) Will include combination of circuit design and design report.

Nano Sensor Principles and Applications

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote nano sensor principles and applications and skills/competencies to design a multi-function board-level micro systems using embedded software, hardware design technology, signal detection and processing technology. The course covers the basic theory of micro-nano sensors and the application of sensing technology. It also discusses the micro-nano processing method of the micro-nano sensing system.

What you will learn

Analyze modern external signal detection technology
Identify the role of external signal detection and processing
Master the physical structure design of signal detection devices
Evaluate and assess the performance of multi-function board-level micro systems
establish a systematic understanding of the application of various external physical signal acquisition principles

Meet your instructor

Linxi Dong

Course content

Session 1: Introduction and its basic signal
Session 2: Measure physical signals and their data fit
Session 3: The theoretical basis of the sensor (part 1)
Session 4: The theoretical basis of the sensor (part 2)
Session 5: Strain sensor
Session 6: Inductive sensor
Session 7: Capacitive sensor
Session 8: Piezoelectric sensors
Session 9: Magnetic sensors
Session 10: Photoelectric sensor
Session 11: Thermoelectric sensors
Session 12: semiconductor sensors
Session 13: Application example of micro sensor

Teaching methodology

Lectures, questioning and discussion, independent learning, independent research.

Assessment

Midterm report (40%) Will include combination of micro- nano sensors’ principles and openended theoretical questions.
Final written exam (60%) Will include combination of micro- nano sensors’ principles and open-ended theoretical questions.

Microelectronic Device Evaluating and Modeling

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to provide students with a basic understanding of semiconductor device modelling. The course covers the background theory of device modelling, passive and active device model methodology, and device models’ application in advanced EDA tools. It also discusses the characterization method of semiconductor devices for modelling.

What you will learn

 Analyze the compact model structure  Identify the role of EDA tools in the modelling process  Collect the semiconductor characteristics with measurement techniques  Construct a model with the model description language of Verilog-A  Construct a model for passive and active device modelling with modern EDA tools  Evaluate and assess the performance of proposed models

Meet your instructor

Jun Liu

Course content

 Session 1: Introduction of semiconductor device modelling.  Session 2: Establish a model with Verilog-A.  Session 3: Passive device modelling of CMOS process (part 1).  Session 4: Passive device modelling of CMOS process (part 2).  Session 5: Active device modelling of CMOS process (part 1).  Session 6: Active device modelling of CMOS process (part 2).  Session 7: Bipolar device modelling of BiCMOS process.  Session 8: Modeling of MOSFET Devices in CMOS Technology  Session 9: Semiconductor Device Testing and Modeling Based on Agilent IC-CAP.  Session 10: Passive and active device modelling of the compound process.  Session 11: On-wafer measurement techniques of RF semiconductor devices.  Session 12: Devices and Models in Compound Semiconductor Processes.  Session 13: Quality assurance of device model and PDK.

Teaching methodology

Lectures, group discussion for problem-solving

Assessment

 Class assignment (40%) Will include a combination of device model analysis and open-ended theoretical questions.  Final assessment (60%) Will include a combination of device model analysis and open-ended theoretical questions

Novelty Class: FPGA Application Training

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

This course aims to provide the practical process of FPGA application for master students of relevant disciplines through guided teaching and hands-on practice, explore the main new theories and technologies, representative methods and some typical application examples in FPGA application, and track the development trend and hot research direction of modern FPGA application. The course covers the performance analysis and application of the modern FPGA based software and hardware collaborative, and cultivate the practical ability of FPGA.

What you will learn

Identify and summarize the main new theories and technologies in FPGA application.
Analyze the development trend and hot research direction of modern FPGA application.
Test the basic theory and implementation method of modern FPGA application.
Propose and formulate solutions for common problems Common problems in complex applications based on FPGA
Evaluate the software and hardware collaborative design method based on FPG

Meet your instructor

Jiye Huang

Course content

 Session 1: YUV to RGB video displaying (Part 1)  Session 2: YUV to RGB video displaying (Part 2)  Session 3: CRC fast checking (Part 1)  Session 4: CRC fast checking (Part 2)  Session 5: Hardware Language and FPGA technology Learning(part 1)  Session 6: Hardware Language and FPGA technology Learning(part 2)  Session 7: Realization of 256-point FFT (Part 1)  Session 8: Realization of 256-point FFT (Part 2)  Session 9: Self designed comprehensive training project based on FPGA (Part 2)  Session 10: Self designed comprehensive training project based on FPGA (Part 2)  Session 11: Self designed comprehensive training project based on FPGA (Part 3)  Session 12: Practical cases learning  Session 13: Practical cases learning

Teaching methodology

Lectures, group discussion, lab experiment, collaborative learning, independent learning, independent research, project-based learning

Assessment

Midterm exam (40%) Will include combination of exercises and open-ended questions.
Final written exam (60%) Will include course report and physical acceptance (divided into four parts: theory, design, implementation and defense, each accounting for 25% of the final examination).

IC Technology and Progress

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of semiconductor or microelectronic fabrication. The course covers the covers the entire basic unit processes used to fabricate integrated circuits and other devices.

What you will learn

Master the basic principles, methods
Design key microelectronics processes
Experiment the main process equipment and testing instruments
Arrange the manufacturing process of typical integrated circuit chips

Meet your instructor

Tiejun Zhou

Course content

Section 1: introduction of integrated circuit and nanotechnology
Section 2: introduction of semiconductors
Section 3: fabrication of Si wafers
Section 4: chemical mechanical polishing
Section 5: oxidation and doping
Section 6: introduction of vacuum technology
Section 7: film deposition by chemical means
Section 8: film deposition by physical means
Section 9: etching by chemical and physical means
Section 10: lithography
Section 11: ion implantation gettering
Section 12: Chip Package
Section 13: Chip test

Teaching methodology

Lecture, teaching and practice in clean room

Assessment

Midterm Presentation (40%) Will include an introduction and summary of topics relevant to this course
Final course paper (60%) Will include combination of numerical exercises and open-ended theoretical questions.

Integrated Microsystems

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of microelectronic mechanical systems (MEMs) and skills/competencies in the design and performance analysis of typical microelectronic mechanical systems. It also discusses some basic principles, processing technology and design methodology of these systems.

What you will learn

Master basic theory of MEMs technology;
Identify and summarize pros and cons in existing MEMs technology
Experiment basic processing techniques and design methodology of MEMs
Evaluate and assess the performance of MEMs

Meet your instructor

Ningning Wang

Course content

Session 1: Introduction of MEMS
Session 2: Basic principles and common methods of MEMS design
Session 3: Microsystem Design Process
Session 4: Microsystem Design Methods
Session 5: Microsystem Modular Design
Session 6: Microsystem Integrated Design
Session 7: Key Technologies of Microsystem Design
Session 8: manufacturing process of a typical MEMS system
Session 9: Lithography and Etching Technology
Session 10: MEMs sensors
Session 11: Calibration and Self-Calibration of Smart Sensors
Session 12: Typical Microsystem - Lab on a Chip
Session 13: Industry applications.

Teaching methodology

Lectures, independent research, project-based learning

Assessment

Lab assignment (40%) Will include lab assignment and open-ended theoretical questions.
Final written exam (60%) Will include project based essay and open-ended theoretical questions.

Novelty Class: Radio Frequency Practical Training

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

TBA

Course content

Teaching methodology

Assessment

Design and Analysis of RF Transceiver Module

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course is to foster and promote knowledge of RF communication circuits and the simulation software ADS related to the front-end circuit module design of RF communication. The course covers the circuits design, the basic principles including low noise amplifier and power amplifier, broadband amplifier, mixer, oscillator. It also discusses software simulation, circuit optimization design, the layout design with PCB board and processing technology.

What you will learn

Master Basic knowledge in the design, simulation software, and circuit principles.
test the RF circuits
Identify and summarize common problems in circuit debugging
Evaluate and assess the performance of RF communication circuits
Experiment the use of RF test instruments.

Meet your instructor

Zhiqun Cheng

Course content

Session 1: Introduction of RF Transceiver Module
Session 2: Design of low noise amplifier circuits (part 1)
Session 3: Design of low noise amplifier circuits (part 2)
Session 4: Design of power amplifier circuits
Session 5: Design of broadband amplifier circuits (part 1)
Session 6: Design of broadband amplifier circuits (part 2)
Session 7: Design of mixer circuits
Session 8: Design of oscillator circuits
Session 9: Process and design of PCB circuits (part 1)
Session 10: Process and design of PCB circuits (part 2)
Session 11: Testing and debugging of circuits
Session 12: Practical examples (Part 1)
Session 13: Practical examples (Part 2)

Teaching methodology

Lectures, group discussion for problem solving, independent learning

Assessment

Assignments (30%) Written assignments throughout the course.
Final examination （70%） Will include combination of numerical exercises and open-ended theoretical questions.

Deep learning and AI Application

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

The aim of this course focuses on machine learning models and several key steps of deep learning in the design and performance analysis of the major parts of deep neural network. This course covers image data preprocessing, convolutional neural networks, pooling, activation function design and selection, network construction and training, and analysis of training results.

What you will learn

Analyze and understand the basic knowledge in the field of artificial intelligence
Design networks for specific applications, process data, train and optimize networks
Evaluate and assess the performance of proposed solutions related to Object classification and detection
Construct the engineering needs of artificial intelligence systems with MATLAB or Python

Meet your instructor

Mian Pan

Course content

Session 1: Overview of Machine Learning Framework and Steps
Session 2: Principles and Implementation of Classical Machine Learning Algorithms
Session 3: Machine Learning (ML) Strategies
Session 4: Convolutional Neural Network
Session 5: Convolutional Neural Networks – Programming Practice
Session 6: Basic Algorithms of Deep Learning
Session 7: Deep Convolutional Neural Networks
Session 8: Deep Convolutional Neural Networks– Programming Practice
Session 9: The Object Detection Based on Deep Learning Neural Networks
Session 10: Design and Implementation of the Object Detection Based on Deep Learning Neural Networks Based on Matlab Platform
Session 11: Network Design and Implementation
Session 12: Programming for the Design and Implementation of the Object Detection
Session 13: final project design and field Report

Teaching methodology

Assessment

Assignments (40%) Written assignments throughout the course.
Final examination （60%） Will include combination of numerical exercises and open-ended theoretical questions.

Novelty Class: Antenna Design and Training

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

What you will learn

Meet your instructor

TBA

Course content

Teaching methodology

Assessment

Novelty Class: Practice and application of Internet of Things

Fri, 01 Jan 2021 00:00:00 +0000

Course overview

This course is a follow-up course of Embedded System and Applications. The aim of this course is to promote the knowledge of basic open source hardware and Linux Ability to design and develop environment independently. This course covers Arduino and raspberry PI open-source hardware platform and QT software platform.

What you will learn

Practice systematic training on Internet of Things and maker practiceindependently
Master basic open source hardware and Linux Ability to design and develop environment independently.
cultivate strong innovation ability and comprehensive ability of internet of things
Identify the new situation and demands of source hardware and Linux of enterprises

Meet your instructor

Jiadong CUI

Course content

Session 1: Fundamental: What is Internet of Things
Session 2: State of the Internet of Things
Session 3: Elements of realizing the IoT
Session 4: IoT devices and protocols
Session 5: Open source hardware platform, Arduino and raspberry PI (part 1)
Session 6: Open source hardware platform, Arduino and raspberry PI (part 2)
Session 7: IoT programming with Linux system, commands and programming (part 1)
Session 8: IoT programming with Linux system, commands and programming (part 2)
Session 9: IoT and data analysis and observability
Session 10: Building IoT GUI with QT (part 1)
Session 11: Building IoT GUI with QT (part 2)
Session 12: Industrial practice of IoT
Session 13: The future of the Internet of Things

Teaching methodology

Lectures, group discussion and problem solving

Assessment

Midterm exam (40%) Will include combination of exercises and open-ended questions.
Final written exam (60%) Will include course report and physical acceptance (divided into four parts: theory, design, implementation and defense, each accounting for 25% of the final examination).

低成本微型PMU（μPMU）的开发

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文《低成本微型PMU（μPMU）的开发》介绍了一种面向电网应用的低成本微型相量测量单元（μPMU）的设计、实现与评估。作者为Yazhou Dong，论文于2024年12月提交至塞浦路斯理工大学，旨在应对现代电力配电网络对经济高效、高精度监测解决方案的日益增长需求。论文由Petros Aristidou教授指导，隶属于电气工程、计算机工程与信息学系。

论文首先介绍了电力系统监测中的挑战与机遇，强调了传统SCADA系统的局限性以及PMU的优势。文献综述部分对SCADA、传统PMU和新兴μPMU技术进行了比较分析，突出低成本高精度测量方案的最新进展与持续难题。

主要贡献

全面对比：本论文系统比较了SCADA、PMU和μPMU技术在功能、成本和精度方面的差异，为低成本μPMU的开发提供了明确的理论依据。
硬件与软件设计：详细介绍了硬件和软件组件的设计方法。硬件部分涵盖了控制单元、信号处理电路、数据采集模块和无线通信系统的选择与集成。软件部分涉及系统架构、GPS数据解析、信号采集算法和无线数据传输。
算法实现：论文实现并测试了包括插值离散傅里叶变换（IPDFT）在内的先进相量测量算法，在保持系统低成本的同时提升了测量精度。
实验验证：通过大量测试评估了所开发μPMU的性能，包括硬件功能测试、同步数据采集、电压电流测量精度和误差分析。对比表总结了其与现有方案的性能差异。
云端集成：论文还探讨了基于云的数据管理，实现了测量数据的可扩展远程访问，这对于现代智能电网应用至关重要。

影响与相关性

本论文通过展示如何利用低成本硬件和开源软件实现高精度相量测量，为电力系统监测领域做出了重要贡献。这为中小型公用事业和预算有限的发展中地区普及先进电网监测技术提供了可能。

论文为硬件和软件的详细设计提供了蓝图，为有意在实际配电网络中部署μPMU的研究人员和工程师提供了宝贵参考。云端集成进一步契合了数字化和智能电网发展的趋势。

本研究通过提供经过验证、可扩展且经济实用的PMU替代方案，填补了文献空白。其成果有望加速μPMU的应用，提高电网可靠性，并通过增强态势感知和数据驱动决策支持可再生能源的集成。

功率电子系统中Si IGBT与SiC MOSFET的紧凑模型开发与验证

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由Yifan Li在塞浦路斯理工大学完成，研究了两类关键半导体器件——硅绝缘栅双极型晶体管（Si IGBT）和碳化硅金属氧化物半导体场效应晶体管（SiC MOSFET）——的紧凑模型开发与验证。这些器件因其高效、开关速度快和鲁棒性强而广泛应用于现代功率电子系统。论文隶属于电气工程、计算机工程与信息学系，体现了功率电子建模领域的多学科交叉。

主要贡献

全面的紧凑建模：本论文开发了基于物理的Si IGBT和SiC MOSFET紧凑模型。这些模型能够在多种工作条件下准确反映器件的电气行为，为功率电子电路的可靠仿真与设计提供支持。
验证与基准测试：所开发模型经过实验数据和行业标准基准的严格验证，确保模型不仅理论准确，也具备实际应用价值。
系统级仿真应用：通过将紧凑模型集成到系统级仿真环境中，论文展示了其在预测功率变换器及其他功率电子系统性能方面的有效性。这对于工程师优化系统效率、可靠性和成本至关重要。
关注新兴技术：论文对SiC MOSFET的研究凸显了其在高压高频应用中的优越性能，顺应了功率电子领域向碳化硅技术转型的趋势。

影响与相关性

本论文为功率电子领域提供了坚实、可验证的模型，服务于学术界和工业界。准确的紧凑模型对于功率电子系统的快速原型开发和优化至关重要，有助于缩短开发周期和降低成本。论文同时关注Si IGBT与SiC MOSFET，确保研究成果适用于从可再生能源系统到电动汽车和工业自动化等广泛应用。

此外，该研究支持了功率变换技术向更高效、更可靠方向的持续转型，契合全球能源可持续与电气化趋势。通过弥合器件物理与系统级性能之间的鸿沟，论文为未来功率电子设计与仿真创新奠定了基础。

基于CYTOP光纤布拉格光栅的心脏健康检测传感器研究

Sun, 01 Jun 2025 00:00:00 +0000

概述

本论文由塞浦路斯理工大学的Hu Yuchi撰写，研究了利用基于CYTOP的光纤布拉格光栅（FBG）技术开发和应用的的心脏健康检测传感器。该工作位于光学工程、生物医学传感和材料科学的交叉点，专注于CYTOP聚合物光纤的独特性质及其在基于FBG的传感器系统中的集成。该研究解决了对非侵入性、高灵敏度和可靠的心脏监测解决方案日益增长的需求，利用聚合物光纤布拉格光栅相对于传统硅基对应物的优势。

主要贡献

CYTOP FBG传感器的设计和制造: 本论文详细描述了在CYTOP聚合物光纤中刻写布拉格光栅的过程，突出了材料良好的机械柔韧性、生物相容性和对物理参数（如应变和压力）的敏感性。该工作探索了与聚合物光纤中光栅刻写相关的挑战和解决方案，由于较低的杨氏模量和不同的光敏特性，这些光纤与传统硅光纤显著不同。
传感器表征和性能分析: 进行了全面的实验研究，以评估CYTOP FBG传感器对心脏相关生理信号的响应。本论文提供了传感器对应变、压力和温度敏感性的数据，特别强调其在检测脉搏波和其他心脏健康指标中的应用。这些传感器的性能与现有技术进行基准测试，展示了增强的敏感性和灵活性，这对可穿戴和植入式医疗设备至关重要。
心脏监测中的系统集成和应用: 该研究包括将CYTOP FBG传感器集成到原型心脏监测系统中。它讨论了从传感器数据中提取有意义的心脏健康指标的信号处理技术，解决了降噪、温度补偿和实时监测等问题。本论文还探索了多参数传感的潜力，利用FBG技术的多路复用能力同时监测各种生理参数。

影响和相关性

本论文的发现对生物医学传感和健康监测领域具有重要意义。通过证明基于CYTOP的FBG传感器在心脏健康检测方面的可行性和优势，该工作为开发下一代可穿戴和植入式医疗设备铺平了道路。这些传感器提供改善的患者舒适度、更高的敏感性以及连续、实时监测生命体征的潜力。该研究有助于聚合物光纤技术在医疗保健中的更广泛采用，解决了传感器制造、集成和数据解释方面的关键挑战。最终，这项工作通过实现更准确和可访问的心脏监测解决方案，支持个性化医学和预防性医疗保健的进步。

基于ETSformer神经网络的室内空气质量预测与改善策略

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由Zhou Zhou于2025年6月在塞浦路斯理工大学完成，探讨了使用ETSformer神经网络预测室内空气质量（IAQ）并制定改善策略。该研究隶属于电气工程、计算机工程与信息学系，体现了结合环境科学、机器学习和工程学的多学科方法。本论文解决了对准确IAQ预测和缓解室内环境空气污染可操作策略的日益增长需求，这对公共卫生和环境管理至关重要。

主要贡献

ETSformer神经网络应用：本论文利用ETSformer神经网络架构（一种用于时间序列预测的最先进模型）来预测IAQ水平。这种方法基于基于transformer模型的最新进展，这些模型在捕获环境数据中复杂的时空依赖性方面表现出色。
IAQ改善策略开发：除了预测之外，本论文基于模型输出提出了改善IAQ的实用策略。这些策略针对真实世界场景定制，考虑了技术可行性和对居住者健康和舒适度的潜在影响。
数据源集成：该研究集成了多个数据流，包括传感器测量和上下文信息，以增强IAQ预测的鲁棒性和准确性。这种整体数据驱动方法为建筑管理和政策干预提供了更可靠的决策支持。
评估与验证：本论文包括对ETSformer模型预测性能的综合评估，与现有方法进行基准测试。结果显示了预测精度的显著改进，突出了基于transformer的神经网络在环境应用中的潜力。

影响与相关性

本论文的研究成果对学术研究和实际实施都具有重要意义。通过证明ETSformer神经网络在IAQ预测中的有效性，该工作为环境监测中机器学习方法的进步做出贡献。提出的改善策略为利益相关者（包括建筑管理者、政策制定者和健康专业人员）提供了可操作的见解，旨在减少室内空气污染及其相关健康风险。

此外，先进神经架构与真实世界IAQ管理的集成体现了跨学科解决方案应对复杂环境挑战的潜力。随着全球对室内空气质量的关注持续上升，特别是在城市化和室内时间增加的背景下，本研究为该领域提供了及时且有影响力的贡献。

基于LoRa无线技术的海上海洋环境浮标监测平台设计

Sun, 01 Jun 2025 00:00:00 +0000

概述

本论文提出了一个基于LoRa无线技术进行数据传输的海上海洋环境浮标监测平台的设计与开发。该研究背景为海洋环境中对实时、可靠且经济高效的环境监测需求的不断增长。传统海洋监测系统通常依赖蜂窝或卫星通信，这些方式成本高昂且受覆盖范围限制，特别是在偏远的海上位置。通过利用LoRa（长距离）无线技术，所提出的平台旨在克服这些挑战，实现从海洋浮标进行长距离、低功耗且可扩展的数据采集。

本论文由Rui Zheng撰写并提交至塞浦路斯理工大学电气工程、计算机工程与信息学系。该研究解决了在恶劣海洋环境中部署配备传感器的浮标的技术要求和操作约束，重点关注稳健通信、能源效率和系统可靠性。

主要贡献

系统架构：本论文详细描述了监测平台的架构，该架构将多个环境传感器与支持LoRa的通信模块集成。这种设置使浮标能够收集水质、温度和其他相关环境参数的数据，并通过无线方式长距离传输到中央网关或基于云的系统进行分析。
LoRa无线集成：一个重要贡献是将LoRa技术适配到海洋应用中。该平台展示了LoRa的长距离、低功耗特性特别适合海上部署，而传统通信网络在这些地方不可用或不可靠。论文讨论了硬件选择、网络拓扑和数据传输协议的优化，以确保高效可靠的运行。
能源管理：该设计集成了节能策略，包括低功耗电子设备和可再生能源（如太阳能板）的潜力，以延长运行寿命。这对于在偏远位置最小化维护并确保连续数据采集至关重要。
原型制作与测试：该研究包括浮标平台的原型制作和现场测试，以验证系统性能。结果证明了在海洋环境中使用LoRa进行实时、连续环境监测的可行性，在显著距离和挑战性条件下实现可靠的数据传输。

影响与相关性

本论文通过为海上数据采集提供实用、可扩展且经济高效的解决方案，为海洋环境监测领域做出了实质性贡献。LoRa技术的使用解决了现有系统的关键限制，显著降低了运营成本并将监测覆盖范围扩展到以前因通信限制而无法访问的区域。

该工作对海洋研究、环境保护机构和海事行业的利益相关者具有高度相关性，这些机构需要准确及时的环境数据用于决策制定、法规合规和生态系统管理。该平台的模块化设计允许轻松适配各种监测需求，支持广泛的传感器类型和部署场景。

通过证明基于LoRa的海洋监测的可行性，本论文为在海洋学研究和环境管理中更广泛采用物联网技术铺平了道路。其发现可为智能浮标网络、实时数据分析和集成海洋观测系统的未来发展提供指导，为可持续海洋资源管理的进步做出贡献。

基于NDVI时间序列的特罗多斯山植被动态预测研究

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文研究了使用归一化植被指数（NDVI）时间序列分析预测特罗多斯山植被动态。NDVI是一种广泛使用的遥感指标，用于量化植被绿度和健康状况，是监测生态变化、土地覆盖和环境干扰的宝贵工具。该研究背景为特罗多斯山，这是塞浦路斯具有生态和气候重要性的地区，旨在利用历史NDVI数据来理解和预测植被随时间的变化趋势。

主要贡献

综合NDVI时间序列分析：本论文汇编并分析了特罗多斯山多年收集的NDVI数据。通过检查时间模式，该研究识别了植被覆盖的季节性和年际变化，为该地区的生态动态提供了详细图景。
预测建模应用：采用先进的统计和机器学习技术，基于历史NDVI时间序列建模和预测未来植被动态。这包括趋势分析、异常检测以及使用长短期记忆（LSTM）网络等预测算法，这些算法特别适合序列数据，在生态预测方面显示出前景。
环境驱动因素评估：该研究探索了NDVI趋势与环境变量（如气候、土地利用和干扰事件（如野火、干旱））之间的关系。通过将NDVI波动与这些因素相关联，本论文增强了对地中海山地生态系统中植被变化驱动因素的理解。
区域重点和方法严谨性：专注于特罗多斯山，该研究提供了特定区域的见解，同时采用鲁棒的数据预处理、验证和统计测试来确保其发现的可靠性。

影响与相关性

本论文的研究成果对塞浦路斯和类似地中海地区的环境监测、土地管理和气候适应策略具有重要意义。通过证明NDVI时间序列在检测和预测植被变化方面的实用性，该研究提供了一个可以适配其他面临生态压力地区的方法框架。

研究中开发的预测模型可以为政策制定者和土地管理者提供关于退化风险区域或需要保护干预区域的信息。此外，遥感数据与先进分析的集成支持向数据驱动的环境决策制定转型。本论文还为机器学习在生态预测中应用的不断增长的文献做出贡献，突出了使用卫星衍生指数进行长期环境评估的机遇和挑战。

总之，该工作推进了对特罗多斯山植被动态的理解，展示了NDVI时间序列分析的力量，并为可持续土地和生态系统管理提供了可操作的见解。

基于YOLO模型的集装箱视频记录破损封条检测

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由塞浦路斯理工大学的Sijun Yu撰写，研究了使用视频记录和深度学习技术对集装箱破损封条进行自动检测。该研究背景为供应链安全，其中确保集装箱封条的完整性对于防止篡改、盗窃和未授权访问至关重要。本论文利用YOLO（You Only Look Once）模型，这是一种最先进的实时目标检测框架，来解决在多样化和潜在复杂的视觉环境中识别受损封条的相关挑战。

主要贡献

YOLO在封条检测中的应用：本论文将YOLO模型适配到从视频片段检测集装箱破损封条的具体任务中。这涉及定制模型架构和训练过程，以识别指示封条破损的细微视觉线索，由于不同的光照、角度和遮挡，这可能具有挑战性。
数据集创建与标注：一个重要贡献是组装和标注包含完整和破损状态下集装箱封条视频帧或图像的数据集。该数据集为训练和评估检测模型奠定了基础，确保其能够泛化到真实世界场景。
性能评估：本论文严格评估了适配YOLO模型的性能，可能使用精确率、召回率和平均精度（mAP）等指标。结果证明了模型在准确高效识别破损封条方面的有效性，突出了其在操作环境中部署的潜力。
自动化与实时分析：通过利用YOLO的实时检测能力，所提出的系统实现了从视频流对集装箱封条进行自动化、连续监测，减少了人工检查的需求并提高了安全检查的可靠性。

影响与相关性

本论文中提出的研究对物流、运输和供应链安全具有重要意义。破损封条的自动检测增强了组织快速识别和响应安全漏洞的能力，最小化损失并保持法规合规性。深度学习和视频分析的使用代表了一种现代、可扩展的方法，可以集成到现有的监控基础设施中。

此外，本论文为将计算机视觉和人工智能应用于工业和安全应用的不断增长的工作做出贡献。通过证明YOLO模型在专门检测任务中的适应性，该研究为进一步改进开辟了途径，如整合视频序列的时间信息、提高对环境变化的鲁棒性，以及扩展到其他形式的篡改检测。总的来说，本论文体现了人工智能驱动自动化在关键安全领域的实际好处。

基于不同预处理方案的前列腺超声图像纹理分析

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文研究了纹理分析技术在前列腺超声图像中的应用，特别关注不同预处理方案如何影响分析结果。该研究在塞浦路斯理工大学进行，解决了医学成像中的一个关键需求：通过先进的图像处理方法提高前列腺癌检测的诊断准确性和可靠性。该研究由Christos P. Loizou指导，位于电气工程、计算机工程和信息学系。

主要贡献

预处理方案的综合评估: 本论文系统比较了应用于前列腺超声图像的多种预处理方法。这些方案可能包括降噪、对比度增强、归一化和滤波，每种方法都可能显著影响从图像中提取的纹理特征的质量和可解释性。
纹理特征提取和分析: 该研究探索了各种纹理描述符——如统计、结构和基于模型的特征——来量化前列腺内的组织特征。通过分析预处理如何影响这些特征，本论文为稳健纹理分析的最佳工作流程提供了见解。
实验验证: 使用前列腺超声图像数据集，本论文评估了不同预处理和纹理分析组合的性能。评估了特征鲁棒性、判别能力和临床应用潜力等指标，为未来研究中选择预处理策略提供了数据驱动的基础。

影响和相关性

本论文的发现对医学成像的研究和临床实践都具有重要意义。通过阐明预处理对纹理分析的影响，该工作指导从业者和研究人员建立更可靠和可重现的图像分析管道。这对前列腺癌诊断特别相关，其中超声图像中的细微纹理差异可能表明病理变化。该方法和结果可以扩展到其他器官和成像模式，为计算机辅助诊断的更广泛领域做出贡献。最终，本论文支持开发用于前列腺癌早期检测和表征的自动化、客观工具，具有改善患者结果和优化医疗资源的潜力。

基于多样化预处理策略和多输入架构的超声图像增强自动前列腺分割

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由Jiale Hou撰写，于2025年5月提交给塞浦路斯理工大学，解决了超声图像中自动前列腺分割的挑战。前列腺分割是计算机辅助诊断和治疗计划（包括癌症在内的前列腺相关疾病）的关键步骤。超声成像由于其非侵入性和实时能力，在临床环境中被广泛使用。然而，超声图像中固有的噪声、低对比度和变异性使得准确分割成为一项复杂的任务。本论文提出了利用多样化预处理策略和多输入神经网络架构来提高分割性能的增强方法。

主要贡献

多样化预处理策略: 本论文系统研究并实施了多种预处理技术，以解决超声成像中的常见问题，如斑点噪声、强度不均匀性和边界模糊性。通过优化这些预处理步骤，分割模型的输入数据质量显著提高，从而更好地描绘前列腺区域。
多输入架构: 基于深度学习的最新进展，该工作引入并评估了多输入神经网络架构。这些模型设计用于同时处理输入数据的不同表示或模态，使网络能够学习互补特征和上下文信息。这种方法增强了模型在不同超声数据集和患者解剖结构中的泛化能力。
综合评估: 本论文包括使用临床超声数据集进行的广泛实验验证。报告了定量指标，如Dice相似系数、敏感性和特异性，证明了所提出方法相对于传统单输入和不太复杂的预处理方法的优越性。
临床相关性: 通过专注于稳健和自动化的解决方案，该研究旨在减少操作员间的变异性，并改善真实世界临床工作流程中前列腺分割的可重现性。

影响和相关性

自动前列腺分割中提出的增强对研究和临床实践都具有重要意义。改进的分割准确性有助于更精确的诊断、治疗计划和前列腺疾病监测。先进预处理和多输入架构的集成为医学图像分析（特别是超声等具有挑战性的模态）的未来研究设定了新的基准。此外，本论文中开发的方法可以适应其他器官分割任务和成像模态，扩大其适用性。该工作为利用人工智能改善医疗保健结果的持续努力做出贡献，支持向更个性化和数据驱动的医学过渡。

基于扩散模型的视频超分辨率技术研究

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文探索了扩散模型在视频超分辨率（VSR）问题中的应用，该任务旨在从低分辨率输入重建高分辨率视频帧。该研究位于深度学习进步的更广泛背景下，特别是扩散模型在图像生成和恢复方面的最新成功。该工作在塞浦路斯理工大学电气工程、计算机工程和信息学系进行，由Sotirios Chatzis教授指导。本论文涉及基于扩散的VSR的理论基础和实践实现，全面研究了如何利用这些生成模型来增强视频质量，同时保持时间连贯性。

主要贡献

扩散模型的新颖应用: 本论文研究了扩散模型在视频超分辨率中的应用，基于其在图像处理方面的已证实能力。通过将这些模型适应到视频领域，该研究寻求克服VSR特有的挑战，如保持帧间时间一致性和处理复杂运动模式。
时间一致性分析: 重点确保生成的高分辨率视频帧不仅视觉上令人愉悦，而且时间上连贯。本论文可能探索解决闪烁和运动伪影问题的架构创新或训练策略，这些是VSR任务中的常见陷阱。
实证评估: 该工作包括实验结果，证明基于扩散的方法与传统和其他基于深度学习的VSR方法相比的有效性。评估可能涵盖定量指标（如PSNR和SSIM）和定性评估，展示视觉保真度和时间稳定性的改进。
局限性和未来方向的讨论: 本论文承认扩散模型的计算需求，并讨论优化性能的策略，如高效采样或模型蒸馏。它还概述了进一步研究的潜在途径，包括为真实世界视频内容集成文本指导或领域适应。

影响和相关性

本论文中提出的研究与计算机视觉和多媒体处理领域高度相关，特别是随着高质量视频内容在从娱乐到监控的应用中变得越来越重要。通过证明扩散模型在视频超分辨率方面的可行性，本论文为寻求推动生成模型可能性的不断增长的工作做出了贡献。这些发现对需要高效可靠视频增强工具的行业具有实际意义，方法论见解可以为学术和商业环境的未来发展提供信息。最终，这项工作推进了VSR的最新技术，突出了扩散模型在解决复杂视频处理挑战方面的变革潜力。

基于智能手机IMU传感器与无线技术的行人航位推算（PDR）

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文探讨了利用智能手机惯性测量单元（IMU）传感器结合无线技术开发与实现行人航位推算（PDR）系统。该研究背景为室内定位，其中GPS信号不可靠或不可用。论文在塞浦路斯理工大学工程与技术学院电气工程、计算机工程与信息学系完成，由Michalis Michaelides指导。该研究解决了大型建筑、交通枢纽和工业设施等环境中对准确、实时行人跟踪的日益增长需求。

主要贡献

智能手机IMU传感器集成：本论文利用现代智能手机中嵌入的加速度计、陀螺仪和磁力计来估计行人运动。通过处理原始传感器数据，系统能够推断步数检测、航向和位移，形成PDR方法的核心。
传感器融合算法：采用先进的传感器融合技术来组合多个传感器的数据，减轻单个传感器偏差和漂移的影响。这些算法对于过滤错误读数并提高位置估计的鲁棒性至关重要，特别是在动态和复杂的室内环境中。
无线技术集成：该研究通过集成无线信号（如Wi-Fi或蓝牙）来扩展传统的基于IMU的PDR，为估计轨迹提供周期性校正。这种混合方法解决了仅基于IMU系统的固有漂移和累积误差，提高了长期准确性和可靠性。
综合评估：本论文包括在真实场景中的实验验证，展示了所提出系统在长时间和长距离准确跟踪行人运动方面的有效性。评估突出了与独立基于IMU方法相比在准确性和鲁棒性方面的改进。

影响与相关性

本论文的研究成果对室内定位和导航领域具有重要意义。通过利用无处不在的智能手机传感器并用无线技术增强，所提出的PDR系统为实时行人跟踪提供了经济高效且可扩展的解决方案。这直接应用于个人导航、应急响应、资产跟踪和智能建筑管理。该研究还为传感器融合算法的持续发展做出贡献，解决了传感器漂移、人体运动变化和环境干扰等挑战。随着对精确室内定位需求的持续增长，本工作中提出的方法和见解为学术研究和商业部署的未来发展奠定了基础。

基于混合神经网络的多目标优化设计集成微系统混合针翅微通道散热器

Sun, 01 Jun 2025 00:00:00 +0000

概述

本论文基于混合神经网络多目标优化技术，对集成微系统混合针翅微通道散热器的优化设计进行了全面研究。该工作解决了微电子器件中对高效热管理的日益增长需求，其中高热通量和紧凑的外形因素需要先进的冷却解决方案。通过在微通道内集成混合针翅结构，该研究旨在提高热性能和流体动力学性能，克服传统微通道散热器在传热效率和压降之间经常面临权衡的局限性。

主要贡献

基于混合神经网络的优化: 本论文引入了混合神经网络框架来执行多目标优化，平衡最大化传热（努塞尔数）和最小化压降等竞争目标。这种方法能够识别散热器几何形状的最佳设计参数，包括针翅排列、尺寸和通道配置。
新型混合针翅微通道设计: 该研究探索了结合针翅阵列和微通道优势的创新散热器架构。这些混合设计被证明能显著提高传热表面积，同时减轻增加流动阻力的不利影响，这是传统针翅或仅微通道解决方案的常见缺点。
综合性能评估: 本论文对拟议散热器的热和流体动力学行为进行了详细分析。采用数值模拟和理论建模来评估几何参数对性能指标的影响。研究结果表明，精心优化的混合针翅微通道散热器可以实现最大器件温度和压降的显著降低，从而提高集成微系统的冷却效率和可靠性。

影响和相关性

本研究的成果对微电子学下一代冷却解决方案的设计具有重要意义，特别是在空间和能源效率至关重要的应用中。基于混合神经网络的优化方法为工程师提供了系统探索复杂设计空间并实现平衡性能改进的强大工具。所展示的热管理增强直接有助于高性能微芯片和微系统的可靠性、寿命和运行稳定性。此外，本论文为未来研究先进散热器拓扑结构奠定了基础，如那些结合三周期最小表面或新型晶格结构的研究，这些结构有望在冷却性能方面获得更大的收益。总的来说，这项工作推进了微通道散热器设计的最新技术，并为电子热管理领域的进一步研究和实际实施提供了坚实的基础。

基于物理TCAD模型的射频器件行为建模技术

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文《基于物理TCAD模型的射频器件行为建模技术》对射频（RF）器件行为建模策略的开发和应用进行了全面研究。该研究在塞浦路斯理工大学电气工程、计算机工程与信息学系进行，体现了该机构在电气与计算机工程研究方面的重点。论文由Junwei Ye撰写，Neophytos Lophitis指导，研究于2024年2月在利马索尔完成并提交。该研究解决了对准确、高效且具有物理信息模型的日益增长需求，这些模型能够弥合详细器件级仿真与更高级别电路/系统设计需求之间的差距。

主要贡献

物理与行为模型的集成：本论文介绍了一种利用技术计算机辅助设计（TCAD）模型来指导并增强射频器件行为建模的方法。通过将行为模型建立在物理器件特性的基础上，该方法提高了模型在实际设计场景中的预测准确性和相关性。
射频器件建模技术：该研究系统探索了各种行为建模技术，评估了它们对不同类别射频器件的适用性和性能。论文可能讨论了参数提取、模型验证，以及将物理效应转换为适合电路仿真环境的紧凑模型形式。
案例研究与验证：通过实际案例研究，本论文证明了所提出建模技术的有效性。这些案例研究可能涉及基于TCAD的仿真、传统行为模型与新开发的混合模型之间的比较，展示了在准确性和计算效率方面的改进。
未来研究框架：本论文建立了一个可扩展到其他器件类型和建模挑战的框架，强调了所提出技术的模块化、可扩展性和适应性。

影响与相关性

本论文中提出的研究对从事射频器件设计和仿真的学术和工业界都具有高度相关性。通过弥合详细物理建模（通过TCAD）与实际行为建模之间的差距，该工作为现代射频系统实现了更准确、更高效的设计流程。这在射频器件变得更加复杂并在更高频率下运行时尤为重要，而传统建模方法可能无法满足要求。

本论文为电子设计自动化（EDA）工具和方法论的持续发展做出贡献，支持下一代无线通信、传感和信号处理系统的开发。将物理洞察集成到行为模型中不仅增强了模型保真度，还加速了迭代设计过程，缩短了上市时间并提高了器件性能。本工作中概述的方法和发现有望为该领域的未来研究和开发提供指导，促进器件建模和系统级设计的创新。

基于物联网与区块链的人体健康监测系统

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文《基于物联网与区块链的人体健康监测系统》由Jun Chen撰写，探讨了物联网（IoT）技术与区块链的集成，以开发一个安全、高效且可扩展的人体健康监测系统。该研究背景为远程健康监测需求的不断增长，尤其是在COVID-19疫情和医疗数字化转型的大背景下。论文提交至塞浦路斯理工大学电气工程、计算机工程与信息学系，由Andreas Andreou指导。

主要贡献

系统架构：本论文提出了一种新颖的架构，利用物联网设备进行实时健康数据采集，并通过区块链技术实现敏感健康信息的安全、防篡改存储与共享。该系统旨在解决医疗数据管理中的关键问题，包括隐私保护、数据完整性和可访问性。
安全与隐私：通过采用区块链的去中心化和不可篡改账本，系统确保健康记录免受未授权访问和篡改。这一方法增强了患者信任，并满足严格的数据保护要求。
远程监测与可访问性：物联网的集成实现了持续、远程的健康监测，减少了频繁就医的需求。患者可通过移动设备更新健康状态，医疗专业人员可实时监控患者数据，实现及时干预和个性化护理。
实际部署：论文讨论了系统部署的实际问题，包括设备互操作性、数据同步，以及面向患者和医疗服务者的用户界面设计。同时还分析了系统的可扩展性问题，并提出了优化策略。

影响与相关性

所提出的系统对未来医疗服务模式具有重要意义。通过结合物联网与区块链技术，系统为数字健康领域中最紧迫的数据安全、患者隐私和可扩展远程监测等挑战提供了有力解决方案。该方法在后疫情时代尤为重要，因其可最大限度减少物理接触并支持远程医疗。

本论文为学术界提供了一个可适配、可扩展的综合框架，适用于慢性病管理、老年护理和公共健康监测等多种医疗应用。其对安全性和可用性的重视，使其成为关注新兴技术与医疗创新交叉领域的研究者、从业者和政策制定者的重要参考。

基于硅纳米线阵列的MEMS加速度计研究

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文研究了以硅纳米线阵列为核心敏感元件的MEMS（微机电系统）加速度计的开发与性能。该研究背景为传感器小型化与灵敏度提升，这对于现代消费电子、汽车系统和工业监测等应用至关重要。论文在塞浦路斯理工大学完成，由Kyriacos Kalli教授指导，系统研究了纳米结构材料与MEMS技术的集成。

主要贡献

本论文详细分析了基于硅纳米线阵列的MEMS加速度计的设计、制造与表征。这些纳米线作为主要的能量转换机制，相较于传统块体材料，具有更优的机械和电学性能。
探讨了硅纳米线的独特优势，如高比表面积和可调电学特性，这些特性有助于提升灵敏度并降低加速度信号的检测阈值。
研究包括实验结果和仿真，展示了将纳米线阵列集成到MEMS加速度计结构后性能的提升，包括灵敏度、频率响应和噪声特性，并与传统MEMS加速度计进行了对比。
本论文还解决了制造过程中的挑战，提出了纳米线阵列与标准MEMS工艺可靠集成的解决方案，确保与现有制造基础设施的兼容性。

影响与相关性

本论文的研究成果对传感器技术的未来具有重要意义。通过利用硅纳米线阵列，推动了MEMS器件的小型化趋势，使得加速度计更小型、更灵敏且更节能。这些进步对于可穿戴设备、物联网传感器和高精度仪器等新兴应用尤为相关，对尺寸、功耗和灵敏度有极高要求。

此外，该工作为纳米结构材料在MEMS中的进一步研究奠定了基础，未来可扩展到其他类型的传感器和换能器。性能和可制造性的提升表明，基于硅纳米线的MEMS加速度计有望成为高性能传感领域的新标准，影响学术研究和工业产品开发。

复杂网络的可预测性

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文《复杂网络的可预测性》由Xuetong Zhao撰写，研究了复杂网络行为和演化的可预测性这一基本问题。复杂网络——如社交、生物和技术系统——表现出挑战传统分析方法的复杂结构和动态行为。本论文在塞浦路斯理工大学电气工程、计算机工程与信息学系进行，于2024年2月在Fragkiskos Papadopoulos指导下完成。

该研究解决了网络可预测性的理论和实践方面，探索了基于当前信息预测网络未来状态或结构变化的程度。该研究利用网络科学、统计力学和计算建模的最新进展来分析合成和真实世界的网络数据。

主要贡献

理论框架：本论文为量化复杂网络中的可预测性建立了严格的框架。这包括定义适当的指标和标准，用于评估从当前数据预测未来网络配置或动态的能力。
方法论进展：它引入或适配分析和计算技术——可能包括机器学习、统计推断和随机游走模型——来评估和改进可预测性。该工作还可能比较不同方法在各种类型网络中的有效性。
实证评估：该研究将所提出的方法应用于一系列网络数据集，展示了可预测性如何随网络拓扑、规模和交互性质而变化。结果可能突出哪些结构特征（如度分布、聚类、模块性）增强或限制可预测性。
案例研究：通过检查特定的真实世界网络（如社交、通信或生物系统），本论文说明了其发现的实际意义，展示了可预测性洞察如何为网络设计、干预策略或风险评估提供信息。

影响与相关性

本论文通过澄清预测复杂网络行为的限制和可能性，为网络科学领域做出了重要贡献。理解可预测性对于广泛的应用至关重要，包括流行病建模、基础设施韧性、信息传播和网络安全。通过提供测量和增强可预测性的系统方法，该研究为从事复杂系统工作的科学家和工程师提供了有价值的工具。

此外，这些发现对网络系统的设计和管理具有更广泛的意义。改进的可预测性可以导致更有效的控制策略、更好的资源分配和增强的故障或攻击鲁棒性。因此，本论文作为理论洞察和实际应用之间的桥梁，推进了复杂网络的科学和工程。

多模态医学成像在组织粉碎术和图像融合中的应用

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由Yuhan Lyu在塞浦路斯理工大学完成，探讨了多模态医学成像技术的集成，特别关注其在组织粉碎术和图像融合中的应用。多模态成像是指结合不同成像模式——如超声、磁共振成像（MRI）和计算机断层扫描（CT）——为诊断、治疗计划和监测提供互补信息。组织粉碎术是一种新兴的非侵入性治疗技术，使用聚焦超声脉冲机械性地破坏目标组织，相比传统热消融方法具有优势。本论文解决了利用多种成像模式提高基于组织粉碎术干预的精度、安全性和有效性的挑战和机遇，以及图像融合在改善临床工作流程和结果中的作用。

主要贡献

多模态成像综合回顾：本论文深入回顾了医学实践中多模态成像的现状，突出了单个模式的优势和局限性以及组合使用时的协同效益。讨论了超声和MRI等模式如何集成以改善组织粉碎术治疗区域的可视化和评估，这得到了最新研究的支持。
组织粉碎术应用：该工作的一个重要部分致力于多模态成像在组织粉碎术中的应用。作者研究了实时超声引导结合其他成像技术如何增强组织粉碎术治疗的靶向、监测和评估。这包括使用图像融合来准确描绘治疗区域和监测组织反应，这对研究和临床应用都至关重要。
图像融合技术：本论文探索了各种图像融合方法，详细介绍了它们的实现和改善治疗传递精度的潜力。通过对齐和集成来自不同来源的数据，图像融合使临床医生能够更好地可视化解剖结构和治疗效果，减少不确定性并改善患者结果。

影响与相关性

多模态成像在组织粉碎术中的集成代表了非侵入性治疗技术的重大进步。通过结合不同成像模式的优势，临床医生可以在靶向和监测方面实现卓越的精度，最小化附带损害，并增强治疗的安全性。考虑到组织粉碎术治疗各种实体器官恶性肿瘤的最近临床批准和持续试验，本论文中提出的研究特别相关。讨论的方法和见解有可能影响未来的临床方案，推动图像引导治疗的创新，并促进非热、非侵入性治疗选择在肿瘤学及其他领域的更广泛采用。此外，对图像融合的关注解决了复杂医疗程序中改善可视化和工作流程集成的关键需求，强调了本论文的实践和转化意义。

真实世界网络双曲嵌入方法比较：机器学习与网络科学

Sun, 01 Jun 2025 00:00:00 +0000

概述

本论文由塞浦路斯理工大学的Zhou Haojie撰写，对应用于真实世界网络的双曲嵌入方法进行了全面的比较研究，重点关注机器学习方法与传统网络科学技术之间的交叉和对比。双曲嵌入已成为表示复杂网络数据的强大工具，能够更高效地分析结构特性并促进下游任务，如链接预测、分类和异常检测。该工作位于两个快速发展的领域——机器学习和网络科学——的交汇处，每个领域都为网络表示和分析提供了独特的方法论。

主要贡献

系统比较：本论文从机器学习和网络科学两个角度系统比较了最先进的双曲嵌入方法。它在各种真实世界网络上评估了它们的性能，考虑了多个下游任务，如映射精度、贪婪路由和链接预测。这种双重视角允许对每种方法论传统固有的优势和局限性进行细致理解。
评估指标：该研究采用了一系列定量指标来评估嵌入质量，包括计算复杂度、可扩展性以及对度分布、模块性和聚类系数等网络特征的敏感性。通过这样做，它提供了不同嵌入策略在多样化网络条件下如何表现的整体视图。
方法集成：本论文探索了将数据驱动的机器学习模型与基于模型的网络科学方法集成的潜力。它突出了机器学习方法的灵活性，这些方法不依赖于强生成假设，并与网络科学模型的可解释性和理论基础形成对比。该工作还讨论了多层网络嵌入的最新进展以及使用庞加莱圆盘模型来改善几何表示和可解释性。
实践洞察：通过大量实验，本论文识别了嵌入精度、计算效率和适用于不同类型网络之间的实际权衡。它为从业者基于特定网络属性和分析目标选择适当的嵌入方法提供了指导。

影响与相关性

本论文对双曲网络嵌入的理论和实践理解做出了重要贡献。通过弥合机器学习和网络科学之间的差距，它推进了网络表示学习的最新技术，并为从事复杂网络数据工作的研究人员和从业者提供了可操作的见解。这些发现在社交网络分析、生物网络建模、网络安全以及理解网络系统潜在几何形状至关重要的任何领域都特别相关。本工作中建立的比较框架和建议有望为更鲁棒、可扩展和可解释的网络嵌入算法的未来研究和开发提供信息。

聚焦超声中磁共振测温方法的改进

Sun, 01 Jun 2025 00:00:00 +0000

概述

本硕士论文由Yu Weng在塞浦路斯理工大学完成，研究聚焦超声（FUS）治疗中改进磁共振（MR）测温的先进方法。MR测温是一种非侵入性成像技术，能够在高强度聚焦超声（HIFU）等热疗过程中实现实时温度映射。这些治疗越来越多地用于精确消融病理组织，包括肿瘤，而无需手术切口。磁共振成像与聚焦超声的集成使临床医生能够监测和控制热能的传递，确保疗效和安全性。然而，MR测温面临一些技术挑战，特别是在动态或异质性组织环境中，本论文旨在解决这些问题。

主要贡献

当前MR测温技术分析：本论文全面回顾了现有MR测温方法，包括广泛使用的质子共振频率（PRF）偏移技术，并讨论了其在组织运动、磁场变化和磁化率变化存在时的局限性。
提出的改进：基于已识别的局限性，本论文探索了先进的采集和处理策略，如并行成像、稀疏采样和鲁棒信号处理算法。还评估了多基线、无参考和混合测温技术，这些技术在挑战性场景中提高了测量精度。
运动跟踪与补偿：认识到器官运动（如肝脏、肾脏或心脏）的影响，该工作研究了运动跟踪解决方案，包括解剖图像图谱、光流位移检测、导航回波和快速血管跟踪。这些技术对于在温度监测期间保持空间精度至关重要。
替代成像方法：本论文回顾了基于MR的替代方法，如MR声辐射力成像（MR-ARFI），可以识别焦点和声束路径，为传统测温提供补充方法，特别是在异质性或经颅应用中。

影响与相关性

本论文提出的进展对图像引导热疗领域具有重要意义。通过提高MR测温的鲁棒性和准确性，特别是在存在运动或复杂组织环境时，这些方法增强了聚焦超声治疗的安全性和有效性。先进运动补偿和替代成像策略的集成拓宽了MR引导FUS的临床适用性，使更广泛的解剖目标能够以更高精度进行治疗。最终，该研究为非侵入性治疗技术的持续发展做出贡献，支持更好的患者结果，并扩大MR引导干预在现代医学中的作用。

首批学生抵达塞浦路斯！

Sun, 01 Sep 2024 00:00:00 +0000

我们欢迎首批抵达塞浦路斯攻读电子科学与技术硕士的学生！

我们很高兴欢迎19名国际学生加入我们，他们将在这里进行为期一年的学习，完成电子科学与技术硕士学位。这些才华横溢的个体将在以下多样化领域进行开创性研究：

🔬 磁共振引导聚焦超声

🌐 智能港口预测性维护

📦 集装箱破损封条检测

⚡ 高功率开关器件

🔍 前列腺癌预测

🚁 无人机室内定位与导航

💧 微流控中的流体冲击

🌱 作物健康监测

🔒 基于区块链的物联网安全

🖼️ 文本到图像的稳定扩散模型

💡 生物医学应用的光纤传感器

我们期待他们为我们的社区带来的创新贡献。欢迎来到CUT！🎓✨

#CUT研究 #创新 #电子科学 #欢迎学生 #全球合作

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