graphic design research essay

Graphic Essays and Comics

Overview | Recommended Software | Student-Made Examples | Other Examples | Instructional Video

A graphic essay (sometimes called a visual essay) uses a combination of text and images to explore a specific topic. Graphic essays can look like comics, graphic novels, magazines, collages, artist books, textbooks, or even websites. Graphic essays often first take the form of written essays and then have graphic elements added to enrich the reader experience. Unlike infographics, which also combine text and images, graphic essays are often more text-based and usually have a narrative arc or specific reading order.

Comics are a genre used to express ideas through images combined with text or other visual information. Comics can take the form of a single panel or a series of juxtaposed panels of images, sometimes called a strip. Text is conveyed via captions below the panel(s), or speech bubbles and onomatopoeias within the panel(s), to indicate dialogue, narration, sound effects, or other information. Graphic novels are often considered to be a longer form of comics, typically in book form.

A web-based graphic essay can take the form of a blog or a single page website, such as a Microsoft Sway page or an interactive Prezi. For Microsoft Sway and Prezi graphic essays, see the examples below. If you are creating a blog we recommend visiting the Web-Based Projects page .

Graphic Essay Design Tip: Graphic essays can take many forms, so we recommend being creative within the scope of your project! Get some help from DesignLab to brainstorm options and talk through the various tools available!

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Recommended Software

There are many different software programs that can be used to create graphic essays. Below is a list of the software that we recommend for making a graphic essay. We organized the software by category and put the software from top to bottom from best to worst. We recommend using a software you know well or learning the software well enough to establish an easy workflow, so you can spend less time troubleshooting and spend more time on your project. Check out our Software Support page for links to tutorials for all of these programs.

General Graphic Essay Software

Web-Based Graphic Essay Software

Comic-Specific Graphic Essay Software

Student-Made Examples

Print style graphic essay.

Becoming a Witness by Jessica Posnock

Creative Graphic Essay

Virtual Communication by Max Hautala *Award Winning*

Curb Magazine (2012) by Journalism 417

Web-Based (Magazine) Graphic Essay

Curb Magazine (Current) by Journalism 417

Web-Based (Sway) Graphic Essay

Language Influences Culture, Thoughts, and Identity by Kristen Luckow *Award Winning*

Language Influences Culture, Thoughts, and Identity Thumbnail Image

Dyslexia by Maria Swanke *Award Winning*

Other Examples

Web-based (blog) graphic essay.

Switch It Up: Graphic Essay by Amanda Zieba

Sceeenshot of Switch It Up Graphic Essay

Graphic Novel

Graphic Novels in the Classroom by Gene Yang

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AIGA Design Archives AIGA Design Archives is one of the richest online resources available to those who practice, study and appreciate great design. It represents the quality of work being created, as well as shifting aesthetics and sensibilities of the designers of the day. Included in this resource are more than 20,000 selections from AIGA’s annual juried design competitions dating from 1924 through the present.

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Recommended periodicals

Journals and periodicals

What do you mean by "journals and periodicals"? By this we generally mean anything that is published in a serialized way--think magazines, scholarly journals, newsletters, that sort of thing.

Where can I access them? It depends! For print items, you will find current periodicals located in their own section in the Harris Fine Art Library. Older print periodicals can be found in the general stacks. Online items usually will be findable through a database. If you're having problems browsing periodicals, just ask for help ! or contact me!

General design periodicals

Design issues | print | electronic

The first American academic journal to examine design history, theory, and criticism, Design Issues provokes inquiry into the cultural and intellectual issues surrounding design.

Design principles and practice | electronic

Design Principles and Practices: An International Journal—Annual Review aims to create an intellectual frame of reference, and to support an interdisciplinary conversation on the role of design in society.

Design studies | electronic

Design Studies is a leading international academic journal focused on developing understanding of design processes. It studies design activity across all domains of application, including engineering and product design, architectural and urban design, computer artefacts and systems design

Design week | electronic

The UK's leading online design magazine. Bringing you the latest news and inspiration across graphics, branding, interiors, digital, product, furniture and more.

International journal of design | electronic

The International Journal of Design is a peer-reviewed, open-access journal devoted to publishing research papers in all fields of design, including industrial design, visual communication design, interface design, animation and game design, architectural design, urban design, and other design related fields.

Journal of design strategies | electronic

The Journal of Design Strategies is published by The New School in association with the School of Design Strategies at Parsons School of Design. An international, peer-reviewed journal focused on emerging developments at the nexus of design, business, and social innovation.

Multi | electronic

Multi is an academic peer-reviewed publication that welcomes scholarly manuscripts concerning topical issues related to diversity, plurality, multiplicity as relevant to the practice, research, and critical consideration of design.

Graphic design periodicals (a selection)

Acta graphica | electronic

ACTA GRAPHICA journal publishes scientific research papers, technical papers, reviews, short and preliminary communications, special features and other news from the field of graphical technology, printing and engineering, graphical communication and design, as well as from all basic and applied science fields relevant for graphic technology and arts.

Computer arts | electronic

Computer Arts offers daily design challenges with invaluable insights, and brings you up-to-date on the latest trends, styles and techniques.

Eye | print | electronic

Eye, the international review of graphic design, is a quarterly printed magazine about graphic design and visual culture.

Information design journal | electronic

Information Design Journal (IDJ) is a peer-reviewed international journal that bridges the gap between research and practice in information design.

Novum | electronic

First published in 1924 – novum World of Graphic Design is a leading and influential design magazine. Each month this bilingual journal presents the very best in graphic design, illustration, photo-design, corporate design, paper, packaging, advertising and typography.

Print | print | electronic

PRINT (founded 1940) is where creative people gather to inspire and build design dialogue. Perpetually curious about everything design, we report on, curate and celebrate visual culture, the makers of that culture and the expression of graphic design in all its forms and mediums.

Other relevant periodicals

Adbusters | print

Adbusters is a global collective of poets, punks and philosophers implementing radical design and media strategies to shake up complacent consumerist culture.

Afterimage | print

Founded and launched in 1972 by photographer and curator Nathan Lyons, Afterimage: The Journal of Media Arts and Cultural Criticism has served as an important voice in the media arts.

Communication arts | electronic

Communication Arts is the largest international trade journal of visual communications. Founded in 1959 by Richard Coyne and Robert Blanchard, the magazine's coverage includes graphic design, advertising, photography, illustration, and interactive media.

i-D magazine | electronic

i-D is a British bimonthly magazine published by Vice Media, dedicated to fashion, music, art and youth culture.

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Graphic Design Dissertation Topics & Titles

Published by Grace Graffin at January 4th, 2023 , Revised On August 16, 2023

Looking for some exciting graphic design research topics for your dissertation? We’ve got you covered. Get your graphic design dissertation topics from our experts.

Whether you’re a student or an active professional, graphics design needs you to be spontaneous. This implies possessing the power to return with distinctive and original work once functioning on a client’s project or a graphic design thesis for your lecturer. It’s one profession that depends entirely on creativity.

Graphic design is in the spotlight everywhere in the United States of America. From easy ad ways that we might read on the TV to advanced animation styles and interactive deposit exhibitions.

This helps to produce an array of various opportunities for finishing a fascinating and innovative graphic design dissertation, with there being a variety of various topic square measures that are prone to more analyses.

A graphic design dissertation is conducted to check your information and learning capabilities. In graphic designing dissertations, you may complete your study on the impacts and effects of style components in varied business sectors of the globe. This may assist you in building an understanding of how things are operating within the skilled world.

If you’re dawdling pondering a groundbreaking graphic designing dissertation topic, then you should stop pondering this much. Bobbing up with a dissertation topic isn’t a piece of cake.

It needs considerable expertise and business information to search out that one drawback already there; however, no one highlighted it. Ideation is a robust method that comes before generating a subject for your dissertation.

Your graphic design thesis topic is barely nearly as good as your graphic-style dissertation plan. Each square measure is interconnected.

So, you’re a graphic designing student with complete command over all the main subjects of your field. However, you have got no clue about the way to write a dissertation. The bulk of graphic planning students can relate to it. To return with a graphic designing dissertation topic, you need information and knowledge of dissertation writing.

Another thing to be mindful of when selecting a topic is the availability of literature since undergraduate and graduate-level dissertations . Unlike PhD. Dissertations, have a smaller scope and do not aim to change course or invent a new concept, so the available literature can be of great help in determining the goal, content, and methodology .

The supporting evidence can help you to fortify and strengthen the arguments presented in your dissertation. At ResearchProspect, we make sure that you choose a topic that is relevant, recent, and interesting. We understand the challenges of being a media student, as with each passing day, something new comes up that takes the world by storm.

Considering the dynamic nature of your subject, our team suggests topics that will help in getting approval you’re your professors instantly. You can also get back to us to either edit the topic or add a few missing elements.

Want to know what essay structure and style will work best for your assignment?

Problem fixed! We can write any type of essay in any referencing style. We ensure every essay written is beyond your expectations.

2022 Graphic Design Dissertation Topics

Topic 1: critical interpretation of the effectiveness of using graphic designing in advanced marketing strategies to increase conversion of the target audience by the uk retailers..

Research Aim: The aim of this study is to critically interpret the effectiveness of using graphic design in advanced marketing strategies to increase conversion of the target audience by UK retailers.

Objectives:

To identify the suitability of graphic designing for marketing purposes.
To demonstrate the relevance of using graphic designing in advanced marketing to increase conversion of the target audience in the UK retail sector.
To provide valid recommendations to UK retailers about how they can strategically use graphic designing in advanced marketing practices aiming to increase conversion of the target audience.

Topic 2: Investigating the growing practice of graphic designing to use visual arts in healthcare, an initiative by the NHS.

Research Aim: The aim of this research study is to investigate the growing practice of graphic design to use visual arts in healthcare. For an insightful understanding, the study will focus on the initiative taken by the NHS.

To analyse the relevance of using graphic design to create visual arts specifically for healthcare purposes.
To describe the initiative taken by the NHS for creating visual arts with the help of graphic design and their purposeful utilisation in healthcare.
To recommend strategies to ensure the best level of use of graphic design for creating visual arts in healthcare thereby meeting the goals of the NHS.

Topic 3: A critical study on the current trend of graphic communication by using graphic designs to strengthen brand identity and recognition in the UK online fashion brands.

Research Aim: The present research study aims to describe the current trend of graphic communication by using graphic designs to strengthen brand identity and recognition in UK online fashion brands.

To study the ongoing trend of graphic communication by using graphic designs and their effectiveness.
To examine how the UK online fashion brands rely on graphic communication to strengthen brand identity and recognition by using the means of graphic designing.
To provide a set of recommendations for ensuring the best level utilisation of graphic designs for improved graphic communication.

Topic 4: Examining the benefits of extensive use of graphic designs in branding to ensure cost and time efficiency in UK SMEs.

Research Aim: The aim of this study is to examine the benefits of extensive use of graphic designs in branding that can ensure cost and time efficiency in UK SMEs.

To carry out a discussion on the advantageous effects of graphic designing in the area of marketing.
To determine how branding can be improved by using graphic designs, which leads towards cost and time efficiency in UK SMEs.
To suggest the best possible strategies and ways of using graphic designs to improve time and cost efficiency in UK SMEs.

Topic 5: Critically analyse the relevance of using 3d printing and CAD software by professional graphic designers referring to the practice in the UK construction industry.

Research Aim: The aim of this study is to analyse the relevance of using 3D printing and CAD software by professional graphic designers. The research study will focus on the activities and use of these technologies in the UK construction industry.

To make a clear idea about the use of 3D printing and CAD software by graphic designers.
To shed light on the use of 3D printing technology and CAD software used by graphic designers in the UK construction industry.
To provide valid recommendations to the UK construction companies for helping graphic designers with the use of 3D printing and CAD software.

Graphic Design Dissertation Topics

Topic 1: graphic design and commercial distinctiveness.

Research aim: This dissertation topic can elaborate on how organizations and companies rely on graphics to be distinctive and different brands in the town. You can also emphasize how significant graphic design is to mould your business and increase more sales.

Topic 2: Role of graphic design in web design development

Research Aim: Graphic design plays a vital role in web development. In your dissertation, you can tell how graphic design appeals to the audience and how it can bring traffic to your website. As a graphic designer, you can also tell the history of web development and the role played by a graphic designer.

Topic 3: Visual Hierarchy in Consumers Preception

Research Aim: Visual Hierarchy is one of the most necessary principles behind attractive web design is the distinction between a website that strategically influences user flow that “looks nice.” You can add the importance of visual hierarchy in the design.

Topic 4: Psychology and its effects on Designing:

Research Aim: Psychology data helps build the look which can make users perform the actions they’re expected, like creating an acquisition or contacting the team. Designers may see psychological science as an advanced approach to enhance the look.

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Topic 5: Challenges in graphic designing

Research Aim: There are many challenges that graphic design faces in the industry. You can highlight topics such as Visual Branding and Project direction in your dissertation.

Topic 6: Photographic theory and graphic design.

Research Aim: In this dissertation topic, you can explain which tools are used by graphic designers and photographers. For what purpose tools are used, and what are the similarities in them.

Topic 7: Graphic design in Great Britain of 1978.

Research Aim: In this dissertation topic, you can discuss the evolution of graphic design during this period of Great Britain in 1978. Discuss how these movements increased the passion for graphic design and what its impact was on youth.

Topic 8: The evolution of graphic design in the 20th century.

Research Aim: In this research paper, you can elaborate on how graphic designing was introduced in the 20th century. How people took it, and how did graphic designing become popular.

Topic 9: Graphic design and corporate identity

Research Aim: You can discuss how graphic designing helped in the evolution of corporate identity. Discuss how brand logos helped increase companies sales by graphic designing, also add a part to empower people towards graphic designing.

Topic 10: Graphic design and mass communication

Research Aim: In this dissertation topic, you can tell how graphic design helps send messages to others by different means, i-e: images or videos. You can also discuss how graphic design works in marketing and how far it is successful.

Topic 11: Graphic design with a low budget

Research Aim: Discuss in your dissertation paper the possibilities to create a graphic product with a low budget. You can also name some companies or individuals who make graphic design on a low budget.

Topic 12: Influence of TV on Graphic Design

Research Aim: There was a need for visual language at the time of TV birth . Many individuals worked on this and set the standards that still influence what is shown on TV.

Topic 13: Computer graphic designers

Research Aim: This would be the best topic to discuss how computer graphic designers helped increase the scope of graphic designing. Does this profession still attract people? Does this profession still worth it?

Topic 14: Paul Rand and his graphic design

Research Aim: In this dissertation paper, you may write about this well-known graphic designer who created many memorable logos and made many contributions to graphic designing. You can also quote other designers too who can be an inspiration for others.

Topic 15: Trends in Graphic Designing

Research Aim: Graphic design has so much innovation from the last decade till now. In your dissertation topic, you can discuss some main trends like 3d design and typography, Art deco and Isometric design etc.

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Topic 16: Women and graphic designing

Research Aim: Women have fought for equal chances in every field, like leadership, economic platforms, and politics. You can elaborate on how women are more creative and how they are taking part in graphic designing and making marks.

Topic 17: Development of career path in graphic designing

Research Aim: In your dissertation paper, you can tell that the typical graphic designer career path starts with the junior designer, which leads to senior designers, art directors, motion artists, web developers, and many more careers. You can empower youth to opt for these professions.

Topic 18: Use Of Artificial Intelligence In Graphic Design

Research Aim: AI is one of the most demanding and latest niches in IT. You can elaborate on how AI to help designers to make designs faster, efficiently, and cheaply. Moreover, you can talk about how AI can also take over designing and neglect humanly efforts.

Topic 19: How Graphic Design Revolutionized Product Packaging

Research Aim: Appealing and fanaticizing product packaging can play an essential role in increasing your sales. You can tell how packaging can attract consumers to buy the product. For example, vibrant colours are used in cosmetic packaging

Topic 20: Website Design and Sales

Research Aim: Improving your website’s style will boost its credibility, which will cause multiplied sales for your company. You can add how an appealing website can make your sales double or more increased .

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How to find graphic design dissertation topics.

To find graphic design dissertation topics:

Research recent design trends.
Analyze design challenges or innovations.
Explore cultural or social aspects.
Review design history and theory.
Consider cross-disciplinary ideas.
Select a topic that resonates with your passion and career aspirations.

Graphic Design Dissertation Topics (28 Examples) For Research

Mark Jun 22, 2020 Jun 20, 2020 Graphic Design No Comments

A good graphic designer knows how to attract people by using appealing and innovative work ideas. When working on the thesis, it is important to choose an attractive dissertation topic. To help you out, we have prepared a list of graphic design dissertation topics, which are interesting and useful. The list of graphic design dissertation […]

The following list of graphic design research topics includes some of the most interesting topics to work on. You can select any research topic on graphic design for your project from this list and tweak it a bit to make it yours or you can let us help you in preparing a proposal and brief on the chosen dissertation topic in graphic design.

List of Graphic Design dissertation topics

Studying the evolution of graphic designing during different periods.

A cost-benefit analysis of investing for hiring an experienced graphic designer.

Analysing the main stages of development of the graphic design industry.

An analysis of the role of colours in graphic design: the best and worst choices.

A review of the approaches used by male and female graphic designers.

Exploring the relationship between signage and mobile map for indoor wayfinding.

To study the impact of visual information in service design.

An evaluation of designing career paths in graphic design.

Studying the graphic design theory research and application in advanced technology.

An analysis of the usage of artificial intelligence in today’s graphic design.

Studying the trends in layout design of feature articles in outdoor magazines.

To examine the graphic design as an instrument of identity assertation for indigenous people.

Evaluating the aesthetic values of the two-dimensional visual design structure.

A literature review of the basic graphic designs.

Studying the importance of artistic sensibility in graphic designing.

Analysing the role of brainstorming and mocking up design ideas.

An analysis of the projecting budgets and schedules in graphic designing.

Studying the importance of design education beyond boundaries in the 21st century.

A review of the new perspectives on visual communication design education.

An empirical study of applying narrative theory to graphic design courses.

An investigation of creativity in graphic designing education from psychological perspectives.

Studying the end-users challenge graphic designers intuition through visual-verbal co-design.

An analysis of the trends in graphic design over the past decade.

Exploring the factors that contributed to the evolution of digital art.

A literature review on the graphic novel.

Analysing the relationship between graphic design and pop-culture.

Identification of the qualities that a professional graphical designer must possess.

Exploring the distinctive features of web-design using secondary research.

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112 Graphic Design Dissertation Topics For Your Perfect Assignment

Art students write about graphic design dissertation topics to showcase their impressive and creative thinking skills. As a graphic designer, your role is to plan and practice conveying messages with textual content. And this is the most effective and innovative method to connect with consumers in the current world.

Whether complex website page layouts or simple business logos, graphic design takes different forms. Other visual design examples include posters, magazine covers, and business cards. Writing a dissertation using intricate and unique graphic design topics is essential for learners that want to excel in their career in this sector. It’s also vital to research graphic design to impress potential employers.

This article lists 110-plus graphic design topics while describing the parts that a good dissertation in this field comprises.

Parts of a Good Graphic Design Dissertation

An excellent dissertation in this field comprises several parts that students should focus on when writing. Here’s a breakdown of the primary sections of a dissertation on this subject.

Introduction : A good dissertation about a graphic design topic has an opening that creates an excellent impression while encouraging the audience to read the rest of the paper. The intro should be brief to capture the audiences’ attention. Problem statement : This section highlights the research question and its background. It also tells the readers why the dissertation is essential. Objectives and aim of the paper : This section tells the readers why your topic matters. It explains the intent of your research and your desired outcomes for the project. Methodology : Here, you describe the methods you use to research the topic. Also, highlight the available techniques while comparing them to choose a viable option. For instance, you can include print media, software, and other platform media details for completing your dissertation. Literature review : This part comprises details of previous studies and the scholars behind them. It also has a theoretical framework for the dissertation, providing insights into your starting point, ideas, and concepts. Limitation : In this section, you highlight the scope, ideas, and limitations of your study. Also, you specify the objectives you attained from your research.

Writing a thesis about a graphic design topic requires relevant principles’ knowledge, and strong writing skills. If you are not interested in writing and don’t want to waste your time on a boring task from a professor, you can pay someone to do your assignment and enjoy the activities you love.

General Graphic Design Dissertation Ideas

Graphic design is a growing study field with many organizations establishing departments and offices for expert designers. Here are general ideas to explore when writing a thesis paper in graphic design.

Understanding graphic design
How graphic design influence communications
Qualifications of a professional graphic designer
Is graphic design a career or a passion?
Similarities between conventional photographers and graphic designers’ tools
The essence of colors in graphic design
Comparison between contemporary graphic design and photographic theory
Understanding the visual design principles
How graphic designers affect their field
Factors influencing graphic design
Developmental stages for graphic design
The influence of technology on graphic design
The graphic design’s role in social media
Changes in graphical design tools
Computer graphics’ evolution in the 20th century
Is traditional graphic design critical in the digital age?
The essence of computers in the visual design evolution
Media forms in graphic design
How print styles and typefaces influence the digital age
Graphic design and its role in web design and development

These are general topics to consider when writing a thesis in this field. Pick any idea from this list and investigate it thoroughly before writing.

Best Graphic Design Dissertation Topics

The internet has many ideas to explore when writing a dissertation in graphic design. Here are the best titles to consider for your paper.

Using color psychology to trigger emotions in graphic design
The impact of graphical design tools on the industry
Graphic design and newspaper adverts- How they influence the consumers’ buying behavior
Graphic design and its use in promoting movie festivals
Graphic design and its use in street art and social commentary
How logos and organization branding affect sales
Space and its use in design esthetics
Color theory and its impact on graphic design
Typeset techniques and principles as part of graphic design
Creating environmental awareness using graphic design
Graphic design software trends
Cultural expectations and graphic design
How visual imaging improves understanding
Media design and new graphics
Is desktop publishing dead?
Web animation and graphic design- How they have shaped the internet content
Newspaper ads evolution in the digital era
Personality role in arts
How experts use graphic design to create a set in the film industry
Restaurants and theme design
Graphic design and persuasion elements
Commercial design- How to facilitate feedback when dealing with customers
How visual hierarchy helps in creating customer e-commerce stores’ perception
Art directors as transformational heads
How graphic designs help in making directories
How graphic design has revolutionized modern cinema
Colorful classroom creation

These ideas can be the basis of a fantastic dissertation. Nevertheless, each of them requires adequate time to investigate and gather relevant information.

Exciting Graphic Design Research Topics

Maybe you want to write about an interesting topic in this field. In that case, writing about any of these ideas can be fun.

Unique 10-minute graphic design projects
How animation helps in creating beautiful postcards
How the design language can trigger brand retention in customers’ minds
Classic book cover re-interpretation
Results and effects of graphic design in the consumer markets
How graphic design helps in coloring kids’ books
Secondary research and its use in exploring web design features
Traits of a successful graphic designer
Graphic design and its relationship with the pop culture
How graphic design facilitates the creation of business cards
Literature review of the graphic novel
Graphic design trends over the last decade
Theory application in graphic design
How people perceive visual communication and design education
How artistic sensibility affects the graphic design
How banners facilitate message conveyance
Average budget analysis in graphic design projects
Is graphic design education important?
How appealing products affect consumer choices
Using graphic design to retarget ads and reach the target market efficiently
Graphic design theory application

These are fun topics to consider for a thesis in this field. Nevertheless, perform in-depth research to write a winning paper about these titles.

Senior Thesis Graphic Design Project Ideas

Maybe you need a graphic design title for your senior thesis. In that case, select any of these ideas for your paper.

How to use graphic design to boost e-commerce stores’ sales
How graphic design can help consumers recall your brand
How Apple uses graphic design to influence buying behavior
How marketing agencies use graphic design
Graphic design and commercial distinctiveness
How limited financial plans affect graphics
How graphic designers use psychological triggers to boost customer loyalty
How video filters boost sales and customer attention in graphic designs
How computer graphics evolved in the 20th century
Graphic design and its use by clothing brands
Why logos and visual design matter to businesses
Graphic design and its use in creating a plant identifying application
Gradient logo designs versus flat logo designs
Advertisement and computer graphics- How they alter consumer behavior
How contrast colors affect buying behavior
How graphic design and brochures help businesses to attract more sales
Developing a graphic design career
The impact of graphic design on product packaging
Vehicle wraps evolution and graphic design
Exploring different techniques that graphic designers use to convey messages
Graphical design application in advanced technology

These are some of the best ideas to explore when researching and writing about graphic design. While this may not be a comprehensive list, it has titles college and uni students can choose for their graduate and undergraduate papers.

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Maybe your teacher or professor wants you to write a high-quality paper on a graphic design topic, but you don’t think you can write a winning essay. Perhaps, you don’t have enough time to research and write a successful thesis. In that case, our experts can help you. Our professional team provides custom research, writing, editing, and proofreading services. Our team answers any student that needs help to score the top marks in all academic papers.

We’re ready to handle your assignment, whether you need assistance with an easy, advanced, or controversial paper. We offer quick online writing help to learners across educational levels. Our assignment help London will surely get you the best grades. Whether you’re pursuing a degree program or college education and your supervisor has asked you to write about graphic design, our ENL writers will help you. Start a chat conversation with us, saying, “Please do my dissertation.” Our customer support team will get back to you. Alternatively, please place an order for your dissertation by filling out our contact form.

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Ellen Lupton

Twitter books, a section on theory considers the centrality of the written and printed word to post-structuralism and deconstruction. here, a wide range of design practices are discussed, from the history of punctuation and the origins of international pictograms to the structure of modern typography. a section on media looks at the role of design in mass communications with erudite essays on stock photography, visual journalism, illustration, advertising and vernacular design cultures. the book closes with history, a section organized as a time-line spanning 200 years of design in america. these historical case studies show how the modern profession of graphic design emerged in response to cultural, political and economic developments in the us. , ellen lupton and j. abbott miller design writing research: writing on graphic design princeton architectural press, 1996; paperback issued by phaidon, 1999.

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Graphic Design Masters Theses

RISD’s graduate program in Graphic Design prepares students for professional practice by emphasizing the roles of social context, media and aesthetics in the production of visible language systems. As a reflection of the discipline itself, the program encourages a nimble and intelligent response to constant change and burgeoning technology, while building a strong foundation of formal, aesthetic and analytical knowledge.

Individual thesis investigation is central to the final year of MFA study and culminates in the comprehensive presentation of work representing an original voice for visual and verbal expression of design thinking. The thesis should be equal parts exploration, explanation, provocation and contribution. Guest critics participate throughout the year and in the year-end thesis review, which offers a forum for critical dialogue focused on each student’s contribution to the field of graphic design. All MFA candidates also submit a written thesis and as a group participate in the RISD Graduate Thesis Exhibition , a large-scale public show held annually.

These works are licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 License .

Theses from 2024 2024

ASILI , Husna Abubakar

Graphic Desire , Michelle Belgrod

Never Real Historians , Emily Bluedorn

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This Is For You: A handbook for design students , Gabriel Drozdov

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Methodology

What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about:

Your overall research objectives and approach
Whether you’ll rely on primary research or secondary research
Your sampling methods or criteria for selecting subjects
Your data collection methods
The procedures you’ll follow to collect data
Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative approach	Quantitative approach
	and describe frequencies, averages, and correlations about relationships between variables

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

How much time do you have to collect data and write up the research?
Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

Experimental and quasi-experimental designs allow you to test cause-and-effect relationships
Descriptive and correlational designs allow you to measure variables and describe relationships between them.

Type of design	Purpose and characteristics
Experimental	relationships effect on a
Quasi-experimental	)
Correlational
Descriptive

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Type of design	Purpose and characteristics


Grounded theory
Phenomenology

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling	Non-probability sampling

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Questionnaires	Interviews
	)

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Quantitative observation

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

Field	Examples of data collection methods
Media & communication	Collecting a sample of texts (e.g., speeches, articles, or social media posts) for data on cultural norms and narratives
Psychology	Using technologies like neuroimaging, eye-tracking, or computer-based tasks to collect data on things like attention, emotional response, or reaction time
Education	Using tests or assignments to collect data on knowledge and skills
Physical sciences	Using scientific instruments to collect data on things like weight, blood pressure, or chemical composition

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

Reliability	Validity
	) )

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

How many participants do you need for an adequate sample size?
What inclusion and exclusion criteria will you use to identify eligible participants?
How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

The distribution of the data (e.g., the frequency of each score on a test)
The central tendency of the data (e.g., the mean to describe the average score)
The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

Make estimates about the population based on your sample data.
Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

Approach	Characteristics
Thematic analysis
Discourse analysis

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Simple random sampling
Stratified sampling
Cluster sampling
Likert scales
Reproducibility

Statistics

Null hypothesis
Statistical power
Probability distribution
Effect size
Poisson distribution

Research bias

Optimism bias
Cognitive bias
Implicit bias
Hawthorne effect
Anchoring bias
Explicit bias

A research design is a strategy for answering your research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

Your research questions and/or hypotheses
Your overall approach (e.g., qualitative or quantitative )
The type of design you’re using (e.g., a survey , experiment , or case study )
Your data collection methods (e.g., questionnaires , observations)
Your data collection procedures (e.g., operationalization , timing and data management)
Your data analysis methods (e.g., statistical tests or thematic analysis )

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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The application of machine learning and deep learning in intelligent transportation: a scientometric analysis and qualitative review of research trends.

1. Introduction

2. research methods, 2.1. data collection, 2.2. tools and methods, 2.3. findings, 3. analysis and findings, 3.1. publication outputs, 3.2. co-authorship, 3.2.1. researcher cooperation, 3.2.2. countries, 3.2.3. organizations, 3.3. keyword co-occurrence, 4. qualitative discussion, 4.1. traffic-flow prediction, 4.2. public transportation, 4.3. intelligent traffic data transmission and sharing, 4.4. intelligent transportation system, 4.5. intelligent parking systems.

diverse research methods: studies use various ML and DL techniques, including random forest (RF), CatBoost, LSTM, ANN, CNN, and SVM, supplemented with genetic algorithms and Bayesian regularized NN;
varied innovative points: innovations use contextual data to predict parking utilization rates, integrate renewable energy sources for electric vehicle charging control, and improve intelligent parking rates through advanced DL;
rich empirical conclusions: the results demonstrate that the proposed models and methods significantly enhance parking utilization rates, profitability, accuracy, and reliability.

4.6. Traffic Congestion

4.7. vehicle detection and tracking, 4.8. vehicle identification and license plate number recognition, 4.9. traffic-light and streetlight system, 5. conclusions.

developing more sophisticated data processing algorithms and analysis models through the deep integration of big data and artificial intelligence to enhance traffic management and control;
enhancing information security and privacy protection by innovating encryption technologies and anonymization methods to safeguard personal data;
utilizing ML and other advanced technologies to improve the accuracy of traffic predictions, optimize traffic flow and accident prediction models, and facilitate more precise traffic decisions;
pairing quantum technologies with AI to open new research, development, and implementation opportunities (e.g., combinatorial optimization);
building cross-departmental data sharing and collaboration platforms to enhance overall efficiency and promote optimal information resource allocation;
advancing the development of autonomous vehicle technologies, including autonomous navigation and safe obstacle avoidance systems, will be critical to driving the next wave of innovations in the transportation sector.

Author Contributions

Data availability statement, conflicts of interest, abbreviations.

AM	Activation maximization
ANN	Artificial neural network
APY	Average year of publication
ARI	Adjusted rand index
ATM	Automatic topic modeling
BS	Batch size
BiGRU	Bidirectional gated recurrent unit
BOA	Butterfly optimization algorithm
BSP	Binary space partitioning
BSS	Blind source separation
BSVR	Bayesian support vector regression
BUC	Bottom-up clustering
CNN	Convolutional neural networks
CS	Citation score per author
CSTN	Continuous surface transition network
DAN	Deep adaptation network
DBN	Deep belief networks
DCRFNN	Dynamic convolutional recurrent fusion neural network
DL	Deep learning
DQN	Deep q-network
DT	Document type
EAI	Explainable artificial intelligence
EC	Evolutionary computation
EdRVFL	Enhanced random vector functional link
ELM	Extreme learning machine
FDA	Fisher discriminant analysis
FedSTN	Federated spatial transformer network
FL	Federated learning
GA	Genetic algorithm
GAN	Generative adversarial network
GAS	Gather-apply-scatter
GCN	Graph convolutional network
GCNN	Genetic convolutional neural network
GNN	Graph neural network
GRU	Gate recurrent unit
IDT	Intelligent data transform
IoT	Internet of Things
IRM	Invariant risk minimization
ITS	Intelligent transportation systems
KDE	Kernel density estimation
KNN	K-nearest neighbor
LR	Logistic regression
LSTM	Long short-term memory neural networks
MDN	Mixture density network
MDP	Markov decision process
ML	Machine learning
MLP	Multi-layer perceptron
MLR	Multiple linear regression
MMN	Mismatch negativity
MTLM	Multi-task learning model
MVSNET	Multi-view spatiotemporal network
NB	Naive bayes
NN	Neural networks
NP	Number of documents per author
POA	Probabilistic output analysis
POI	Point of interest
RBF	Radial basis function
RBM	Restricted Boltzmann machine
RCNN	Regions with convolutional neural networks
ResNet	Residual network
RF	Random forest
RNN	Recurrent neural network
SMO	Sequential minimal optimization
SVC	Support-vector classification
SVM	Support-vector machine
TBI	Target bearing indicator
TFP	Traffic-flow prediction
TMS	Traffic management systems
WoS	Web of Science

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Click here to enlarge figure

Up-and-Coming Research Topics	Number of Publications
Traffic-Flow Prediction (TFP)	31
Public Transportation	19
Intelligent Traffic Data Transmission and Sharing	16
Intelligent Transportation System (ITS)	13
Smart Parking	12
Traffic Congestion	7
Vehicle Detection and Tracking	6
Vehicle Identification and License Plate Number Recognition	5
Traffic-Light and Streetlight System	4

Articles	Approach	Research Innovation	Data Preprocessing	Empirical Conclusion	Limitations	Proposed Future
[ ]	SMO, BiGRU	SMO algorithm for hyperparameter adjustment	Min–max normalization approach	SMOBGRU-TP model outperforms the existing technology	-	(1) Combine mixed DL models (2) Improve the efficiency of SMOBGRU-TP method
[ ]	LSTM, RNN	Noise pollution and time-series data for better prediction	Data Interpolation	Adding noise data improves the performance by 13.48%	-	Reduce specialization of sensing infrastructure using feature profiles and AI technology
[ ]	FL, GCNN	Trusted authority principle integrated into federated learning for model data protection	-	FDL-TF outperforms baseline solution	-	-
[ ]	GCN	Study of superparameter optimization of T-GCN	Min–max normalization approach	The superparameter optimizer selects T-GCN’s optimal hyperparameters		-
[ ]	EC, DCRFNN	Short-term traffic-flow prediction model for 5g Internet of vehicles based on EC and DL	-	Ensure good unloading performance and high prediction performance	No suitable task-scheduling algorithm is proposed	Traffic-accident risk prediction
[ ]	RNN, GCNN	Spatiotemporal correlation obtained from traffic network	-	Better than the most advanced baseline model	-	Consider external factors that determine traffic forecasts
[ ]	FedSTN	Privacy issues addressed in distributed traffic data	-	FedSTN has a higher prediction accuracy	-	Real-time path planning through traffic-flow prediction
[ ]	CONV-BI-LSTM	Traffic forecasting using Industry 4.0 and big-data analysis	-	CONV-BI-LSTM is the top choice for short-term prediction	-	-
[ ]	PVHH, IDT, Ford-Fulkerson	Node intelligent prediction is performed on specific nodes	-	Good prediction effect	Problems in prediction accuracy and time	Study of time lag and unpredictable factors
[ ]	EdRVFL, RF, GCN, BOA	Accurate counting of moving targets under different weather conditions	-	This method excels when connections are unavailable or too complex	-	-
[ ]	LSTM	Utilization of large-scale taxi GPS trajectories and environmental information	-	Detection and tracking accuracy increase by 10%, cutting errors by approximately 50%	Weather conditions are described using only qualitative variables, such as sunny and rainy weather	Considering quantitative and human factors
[ ]	RBM, SVM	Application of recurrent mixed density networks for short-term traffic-flow prediction	Map matching algorithm	O-Sense can effectively improve the accuracy of travel cost estimation	-	-
[ ]	LSTM, MDN	Big-data architecture and real-time prediction model proposed	-	This method demonstrates significant superiority	-	-
[ ]	LSTM, GRU	Traffic-flow prediction using technologies such as bagging and air pollution		When assessing January 2020 data, its predictions were highly accurate	COVID-19 impacts prediction accuracy after January 2020	Extend the initiative to the entirety of California
[ ]	KNN	Dynamic correlation of transportation nodes integrated with spatiotemporal DL models	Mean/median method, Z-score, Min–max normalization	Reduce the error rate of traffic-congestion prediction by more than 30%	-	(1) Study of the impact of different seasons on traffic flow (2) Combine satellite traffic measurements with ground-sensor values
[ ]	GCN, Spatiotemporal DL model	Adaptation to high mobility and frequent changes in the network	Z-score normalization	Outperforms state-of-the-art GNN baselines	-	(1) Integrate different GCN-based DL models (2) Integrate the captured features into traffic prediction
[ ]	LSTM	Parameters and operation time reduced	Handling abnormal data	High accuracy is achieved in industrial 4.0 applications	-	-
[ ]	CNN, GNN	High-precision traffic forecasting achieved	Linear interpolation method	Improved results in short- and long-term forecasting	Not considering all kinds of accidents	Consider more factors to improve the model
[ ]	CNN, LSTM, AM, XGBoost	Traffic-flow estimation considering external factors	Min–max normalization approach	The model has low prediction error and performs well	Lack of fine-grained stop point identification for signaling users	-
[ ]	DBN, POA	Initial step towards sensor practicability in urban management	Min–max normalization approach	AST2FP-OHDBN outperforms the current state-of-the-art DL model	-	Design hybrid metaheuristics to enhance prediction results
[ ]	GNN, LSTM	Migration learning is used to address data scarcity		The MSE value of the model is 6.309, MAE value is 2.256, RMSE value is 2.511	Other weather factors and track characteristics are not considered during training	(1) Explore the optimal value of input parameters (2) Consider other factors affecting traffic flow
[ ]	CNN, LSTM	Method proposed for analyzing cellular communication data	Min–max normalization approach	It is the best way to predict traffic flow through traffic counters on the road	SARIMA can only predict for one hour	Plan to test a new anomaly detection algorithm
[ ]	LSTM	Hierarchical information considering spatial interaction	Min–max normalization approach	Mgat model is superior to the most advanced method	-	-
[ ]	GCN, KNN	Complex dynamics and spatial relationship of mobile traffic demand captured	-	Enhance cellular network traffic prediction accuracy significantly		Expand the scope of data collection
[ ]	GCN, GRU	Model learning mechanisms guided by prior domain knowledge	-	Model increased RMSE and MAPE by approximately 8.4–29.5% and 7.5–30.6%	Study of the impact of different spatial embedded networks	-
[ ]	RNN, LSTM	End-to-end solution for capturing cross-domain knowledge automatically	Min–max normalization approach	GASTN can outperform the current state baseline with a faster running time	-	Explore a GCN method for mobile traffic prediction based on a spatial relationship graph
[ ]	GAN	Parallel spatiotemporal DL network for learning features from time and space dimensions	Min–max normalization approach	This method has the highest accuracy, reaching 98.21%	-	Create a model that works effectively in both typical and unusual situations
[ ]	DAN, LSTM	Complex patterns and dynamics of urban transportation systems captured	-	The model has excellent performance in spatiotemporal data migration learning	-	(1) Further apply ST-DAAN to traffic-flow prediction (2) POI recommendation tasks
[ ]	CNN, LSTM	Trusted authority principle integrated into federated learning for model data protection	-	Parallel spatiotemporal DL network outperforms competitors	-	Advanced DL architecture for large-scale traffic-flow prediction
[ ]	RBF	Study on superparameter optimization of T-GCN	Eliminate noise, outliers, and missing values	The method based on depth RBF is superior to the traditional traffic analysis method	The effectiveness of the model in various situations needs to be strictly tested	Study of the applicability of deep RBF networks in other fields

Articles	Approach	Research Innovation	Data Preprocessing	Empirical Conclusion	Limitations	Proposed Future
[ ]	GCN, CNN, LSTM, Res Net	Modeling complex nonlinear spatiotemporal relationships		It shows different prediction accuracy in different regions	There are still deficiencies in the interpretation of the model	Consider improving LSTM and exploring layered attention
[ ]	TBI	Passenger-flow forecast using vehicle GPS records	Data cleaning, matching, and organization	The method outperforms time-series-based predictions for long-term taxi flow.	-	Real-time prediction architecture based on TBI2Flow
[ ]	DNN	Integration of feature engineering technology with deep neural network for effective forecasting	-	The performance gain of the model is 25–37%, which is higher than the most advanced model on the standard benchmark index	-	Expect to perform well in weather forecasting, traffic-speed forecasting, and many other fields
[ ]	RF	Quantitative analysis method for regional shared travel potential mining	-	If carpooling is adopted, the emission-reduction effect can be well reflected	Did not take a personal attitude towards carpooling into consideration	Further investigate the attitude towards carpooling
[ ]	XGBoost, CSTN	Extraction of micro and macro spatial characteristics from urban taxi service demand data	Min–max normalization approach	Multisensory stimulation attention and multi-periodic feature learning are shown to be effective.	-	(1) Expand MSSA by learning more cyclical patterns (2) Merge more context information
[ ]	IDT	Taxi cruise recommendation strategy based on real-time and historical trajectory data		TR-RHT can accurately recommend the cruising route for cruising time reduction	-	-
[ ]	DT, SVC, NB, LR, RF	Transit congestion detection method based on opportunity perception	-	Over 80% congestion can be detected when used by 8–12% of commuters	-	-
[ ]	BuStop	Dwell position extraction from multimodal sensing using commuter’s smartphones	-	The framework can accurately detect various dwell positions	-	-
[ ]	FDA, BSVR	Quantification of uncertainty for robust performance improvement	-	FDA’s predictions are highly accurate and effective at forecasting travel time distribution uncertainty	-	-
[ ]	CheetahVIS	Dynamic bus routes provided to help users identify traffic flow		Proved the effectiveness of CheetahVIS	-	-
[ ]	PubtraVis	New visualization tool developed for public transportation system operation	Data cleaning, reorganization, extraction, and filtering	PubtraVis is a highly beneficial and user-friendly tool	“Ease of use” needs improvement	(1) Use GTFS static data (2) Real-time data to develop additional visual analysis module
[ ]	SVR, RF, Adaboost, GBRT, XGBoost, MLP	Improved accuracy in estimating car-hailing trip mobility	-	This model outperforms other benchmarks in estimating car-hailing trip mobility	Use diverse geographic context features to measure the replaceability of location	Consider individual travel behavior in mobility modeling
[ ]	MVST-NET	Urban big data is used to predict shared bicycle travel behavior	Min–max normalization approach	The model has good performance in various tested models	-	Performance improvement of analytical methods to make them more interpretable
[ ]	Bi-LSTM	Forecasting available bicycles and free slots at shared bicycle stations	-	It provides a powerful method for reliable and fast prediction of available bicycles	-	-
[ ]	BSS	Bicycle rebalancing solution in bike sharing system (BSS)		The proposed method outperforms the relocation manager in terms of bicycle shortage and task difficulty	-	-
[ ]	STOP	Framework proposed for predicting shared station occupancy using Bayesian and association classifiers	-	Shows the usefulness of maintenance actions based on short-term forecasts and readable models	-	Enrich station occupancy data
[ ]	IRM, GNN, RNN	DL-based bicycle-demand forecasting model introduced		The model has higher R2, lower RMSE, and MAE and has a better prediction effect	This study is limited to possible influencing factors	Explore the impact of social population, traffic flow, and weather
[ ]	Attention-Based Model, CNN	Advance prediction of potential destinations for rescheduling artificial bicycles		The proposed framework excels in precision, recall, and F1 compared to top-tier methods	-	Simulate other relevant factors to provide better prediction of shared bicycle destinations

Articles	Approach	Research Innovation	Data Preprocessing	Empirical Conclusion	Limitations	Proposed Future
[ ]	Logistic Regression, ANN, DT, KNN, RF	Predict accident severity using various classification models	-	The average accuracy of the decision tree (DT) model is the highest, which is 71.44%	-	-
[ ]	RNN, GAN, SVM, CNN, MMN	Solve traffic-accident detection issues with semi-supervised DL and different data patterns	-	GAN outperforms other models’ accuracy and classification F1, with or without multimodal data	Focus only on traffic-sensor data and text data	Handle more types of data for other smart-city applications
[ ]	DT, RF, MLR, NB	Discuss a paper on data models for road traffic accidents and propose prediction models		The results are relatively good (the accuracy is 60–80%)	-	Reduce the imbalance ratio of labels before inputting data sets into the model for training
[ ]	BLM, SVM, XGBoost, XAI	Gather high-quality data to infer different factors in urban road traffic accidents	-	SVM shows the highest performance in accuracy and F1 score	-	-
[ ]	XGBoost, CatBoost, LightGBM, DT, RF, Stacked DCL-X	Classify the injuries caused by vehicle–pedestrian and vehicle–obstacle collisions		The overlapping DCL-X model has better stability, less super parameters, and higher accuracy under different training data	-	-
[ ]	Faster R-CNN	Introduce Faster R-CNN to extract IoT electronic data features	-	The faster R-CNN algorithm has stronger robustness and reliability in its data collection and analysis	Electronic traffic data are not clearly classified, and influence factors are not considered	(1) Accurately identify its projects (2) Optimize the designed model to obtain traffic information better
[ ]	GAS, BSP	Address and overcome research challenges in IVN data processing	-	GPU-based graphics processing technology can achieve excellent performance on IVN data	-	Focus on other aspects of IVN data processing
[ ]	Vehiclectron	Propose a new model to accurately estimate road vehicle cuboids using single-view sensors and road geometry information	-	Feasibility and applicability are confirmed via CCTV-captured real-road images	3D box estimation depends on the target-detection model	Provide accurate information in the field of intelligent traffic recognition and control
[ ]	KDE	Build a traffic visualization management system based on improved ML algorithms	-	The method in this paper is critical for smart-city traffic management	-	-
[ ]	BD	Discuss the application of BDA in constructing large-scale sensor data and modeling autonomous vehicles		The feasibility and effectiveness of the model are verified	-	Content-based sensor data management and process
[ ]	ARI, KNN	Develop a method to predict the psychophysiological load affecting driving safety using vehicle manipulation data	Min–max normalization approach	Compared with previous models, the performance of this model is relatively low	-	(1) Collect data from different road environments (2) Evaluate the transferability of the proposed model
[ ]	Bagging, Boosting, ANN	Develop a method to predict high-risk bus drivers as a benchmark for effective bus safety policies	-	The classification accuracy of the model reaches 85%	Focus only on the relationship between dangerous driving behavior and collision	The proposed neural network model can be further improved
[ ]	3D- LTS	Propose a driver yawning detection method based on subtle facial motion recognition	-	It can detect yawning robustness in various external environments	Low image resolution and large camera vibration reduce the effectiveness of the method	Use better image preprocessing methods
[ ]	CNN, SVM	Propose an ML algorithm based on smart devices and IoT network firewalls to protect data traffic	-	The hybrid DL model has effectiveness and high accuracy	-	-
[ ]	EEMR, BUC, TAdam	Design efficient multi-hop routing for intelligent traffic wireless sensor networks	-	It provides a new reference for improving the transmission and sharing efficiency of intelligent transportation data	-	Use edge computing, principal component analysis, and other methods to achieve data dimensionality reduction and rapid processing
[ ]	CNN	Develop a new framework based on artificial intelligence (AI) to predict traffic conditions on densely deployed IoT networks	-	Compared with the existing traditional CNN model, LTP-CNN has higher prediction efficiency	-	-

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	LTSM	Establish ML framework for smart traffic, achieve optimal accuracy	Implementing intelligent transportation systems improves transportation and air quality	-	Explore the impact of intelligent transportation on the environment and supply chain
[ ]	LSTM, Bayesian optimization	Apply DL for traffic pattern detection using smartphone data	Extensive experiments demonstrate a high recognition rate and efficiency	Training requires ample labeled data and computational complexity	The model is more robust to diverse user behaviors and optimized for its computational efficiency
[ ]	DT, RF, ET, XGBoost	Propose an intelligent traffic system for the IOV network with tree ML	High detection accuracy and low computational costs are key features	-	-
[ ]	Hadoop, Spark DL	Introduce City Administration Dashboard for urban traffic analysis	Road network prediction accuracy reaches 94.05%	Suitability, data privacy, and security for specific city environments	-
[ ]	CNN	Implement resource load balancing and DL for real-time scheduling	ATM system outperforms traditional traffic management methods	Applicability to the specific urban environment, generalization ability of model	Improve data processing and transmission efficiency
[ ]	ATM	Enhance travel pattern extraction and path estimation with U-Net and GNN	RMSE, MAE, and MAPE are 4%, 20.49%, and 18%, respectively	Dependence on infrastructure and vehicle equipment	Consider a variety of traffic situations
[ ]	U-Net, GNN	Identify malicious traffic in SDN-based Internet of Vehicles	Enhanced attack detection reduces latency and prevents buffer overflow issues	-	Extend the study to other urban traffic datasets
[ ]	Fuzzy, logic	Introduce the ST-GCRN model for traffic-flow estimation	Bike-sharing system errors reduced by 98% and 63% in the estimation	-	-
[ ]	GCN, LSTM	Propose MTLM model for travel time estimation	Real-world data sets have been extensively experimented on	-	-
[ ]	MTLM	Batam City Government adopts smart mobility for sustainable transportation	Optimal implementation and sustainable approach are yet to be fully realized	-	Extend the datasets to other cities or transit systems
[ ]	Qualitative analysis research method	SafePath algorithm ensures differential privacy with minimal data impact	SafePath enhances efficiency and scalability for large and sparse data situations	-	-
[ ]	SafePath	Establish ML framework for smart traffic, achieve optimal accuracy	Implementing intelligent transportation systems improves transportation and air quality	-	-

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	RF, CatBoost	Evaluate RF and CatBoost for ML	Using context data has a positive impact on parking utilization prediction	-	Use POI data as context data
[ ]	LSTM	Study of electric vehicle presence in urban IoT	Proper EV charging control boosts profits	-	Use renewable energy input in the model
[ ]	LSTM	Identify optimal predictive model in ML and DL	The results obtained improve the existing results in the literature	-	-
[ ]	ANN	Use ANN for parking-space data collection	The proposed method improves the intelligent parking rate through DL	-	Use genetic algorithm and neural network for training
[ ]	LSTM	Develop a mobile smart parking app with DL	High accuracy and reliability	-	Investigate the influence of parking lots on traffic density under different parameters
[ ]	CNN, LSTM, GA	Establish a parking-space availability system	Compared to existing states, this model has better performance	-	Study of traffic density under different parameters
[ ]	ANN, SVM, ARIMA, RNN	Predict available parking in city garages	Bayesian regularized neural network is a reliable and fast time-period prediction method	-	-
[ ]	IoT	Address tourist city parking layout issues	Simple and easy to operate, with low requirements for data accuracy	-	-
[ ]	CNN, ELM	Propose parking-spot detection with CNN and ELM	The CNN elm method outperforms other hybrid CNN models using different classifiers	-	Verify the performance of CNN-ELM on other parking datasets
[ ]	IoT, LSTM	Predict parking availability via IoT, cloud, and sensors	The proposed model is superior to the most advanced prediction model at present	Only parking space occupancy information is considered without considering weather conditions and social events	Consider weather conditions, social event information, and parking-lot occupancy information

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	FITCCS-VN	Remote viewing of road traffic flow and vehicle volume	The system achieves an accuracy of 95% and a miss rate of 5%	-
[ ]	Logit, SVM	Common multivariate outlier detection methods	Outlier detection plays an important role in discovering useful and valuable information	-	(1) Identify variables with high discriminatory power (2) Apply the algorithms to various road types in a smart city
[ ]	DNN	TC2S-DNN model integrates IoT and DL for congestion forecast	The performance of the TC2S-DNN model is reported to be better than previously published approaches	If the information is obtained in delay, or there is too much noise by the signal sensors. It can be influenced by the output of the proposed solution	-
[ ]	Deep double-Q learning	Adaptive traffic signal adjustments based on vehicle types	The average waiting time at intersection points by up to 91.7%	The sampled data is biased and not exactly the same or the same distribution	-
[ ]	Hybrid Neuro-Fuzzy	Enhance congestion prediction accuracy with IoT sensor data	The model has an even higher accuracy of 99.214% during the training phase	-	-
[ ]	AFT	Apply survival analysis methods for congestion assessment	The results show a dramatic improvement in data quality and successful evaluation of traffic conditions with high reliability	-	Apply proposed methods for effective traffic control and management in smart cities
[ ]	C-V2X network	Optimize cellular AP and vehicle throughput with user-AP associations	Results confirm the effectiveness and superiority of the traffic offloading method via DL in CV2X networks	-	-

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	EKF, NN, SVM	Integrating data from GPS augmentation and low-cost DR systems	EKF/SVM trained with particle-swarm optimization is more suitable for localization	GPS quality may decrease in actual situations	Research on vehicle prototype based on Arduino
[ ]	-	Adapt to time-varying and unbalanced tracking workloads caused by traffic dynamics	Shows 100% tracking coverage and real-time assurance	-	-
[ ]	EKF, SVM, RF	Using SVM to overcome the shortage of EKF when the GPS signal is interrupted	Experience 94% improvement over simple EKF prediction	When interrupted, GPS quality will decrease	(1) Test and improve this hybrid solution in case of GPS interruption (2) Combine this method with a distributed algorithm
[ ]	EKF, SVM, Faster R-CNN	An intelligent vision sensor is preset for the detection and tracking of synchronous attitude estimation	Integrating vehicle position and attitude into EKF enhances tracking results	-	-
[ ]	RetinaNet	Using RetinaNet architecture and Cars Overhead with Context dataset to find vehicles in satellite images	The model has good vehicle-detection accuracy and low detection time	-	(1) Expand experimental evaluation and conduct ablation experiments (2) Enhance the model with a street-detection model
[ ]	DNN	A vehicle detection and tracking method in bad weather conditions is proposed	This method is superior to the most advanced method under adverse weather conditions	-	Some hard cases still need more attention and improvement

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	CNN	CNN for vehicle feature extraction	The accuracy of the CNN model was evaluated based on the confidence values of the detected objects	The larger and lower size of the image can affect the validation process	(1) Expand the system to include more vehicle types (2) Improve the accuracy and robustness of the model
[ ]	DLVLPNR model	Fast R-CNN with Inception V2 and Tesseract OCR for license plate recognition	The DL-VLPNR model can achieve optimal detection and recognition performance, as it attained the highest accuracy of 0.986	-	Handle more diverse conditions and integration into real-time applications for smart-city management
[ ]	RCNN	Extending vehicle ID for counting and analysis	The average accuracy of the proposed method is 90.4%	Increasing the number after some time, the network goes into the stage of overfitting, and the accuracy of the network decreases	Optimize the method for enhanced performance
[ ]	Deep active learning framework	Memory space for active learning in vehicle-type recognition	Over 90% accuracy for 20 vehicle types	The sample data is biased and does not have the same distribution	-

Articles	Approach	Research Innovation	Empirical Conclusion	Limitations	Proposed Future
[ ]	RL, DQN	A dynamic discount factor is embedded in the iterative Bellman equation to prevent bias in the estimation of the action value function	The trained agent outperforms the fixed timing plan, cutting total system delay by 20%	-	Apply DRL to multiple intersections
[ ]	RL	Combining speed guidance system with traffic-signal control based on reinforcement learning	The proposed method is superior to a fixed timing plan and traditional drive control	-	(1) Add offset optimization to signal timing optimization (2) Use V2V communication and dynamic velocity guidance strategy
[ ]	MDP, RL	KS-DDPG is proposed to achieve optimal control by enhancing the cooperation between traffic signals	KS-DDPG significantly boosts large-scale traffic network control and handles flow fluctuations effectively	All agents need to communicate, resulting in limited overall communication efficiency	Consider using heterogeneous vehicles to build a more realistic traffic flow

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Zhang, J.; Wang, J.; Zang, H.; Ma, N.; Skitmore, M.; Qu, Z.; Skulmoski, G.; Chen, J. The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends. Sustainability 2024 , 16 , 5879. https://doi.org/10.3390/su16145879

Zhang J, Wang J, Zang H, Ma N, Skitmore M, Qu Z, Skulmoski G, Chen J. The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends. Sustainability . 2024; 16(14):5879. https://doi.org/10.3390/su16145879

Zhang, Junkai, Jun Wang, Haoyu Zang, Ning Ma, Martin Skitmore, Ziyi Qu, Greg Skulmoski, and Jianli Chen. 2024. "The Application of Machine Learning and Deep Learning in Intelligent Transportation: A Scientometric Analysis and Qualitative Review of Research Trends" Sustainability 16, no. 14: 5879. https://doi.org/10.3390/su16145879

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PDF Research in graphic design
Graphic design research excellence resides in monographs and articles about individuals who have made a contribution to the field. The most authoritative and useful accounts derive from ... papers in these volumes reflect graphic design history, theory and practice - the latter embedded though co-design and participatory design methods ...
Research in Graphic Design
Sue Walker is professor of Typography and a former head of the Department of Typography & Graphic Communication and dean of the Faculty of Arts and Humanities at the University of Reading for 10 years. She is a fellow of the Design Research Society and was a member of the art and design sub-panel for Research Assessment Exercise (RAE) 2008 and Research Excellence Framework (REF) 2014, the UK ...
The Rise of Research in Graphic Design
The Rise of Research in Graphic Design. 2006, Design Studies: Theory and Research in Graphic Design. There is an immediate need to clarify and develop the role of graphic design research for the theoretical underpinning of graphic design education. A report that accompanied the 2014 UK Research Excellence Framework (REF2014) described 'the ...
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Graphic design as a knowledge domain is deeply rooted in arts, crafts, and the cultural history of human civilization. However, the research in graphic design is a recent phenomenon and it has ...
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definition onto graphic design as a whole. A formulaic view of graphic design, that the AI research that this article engages with also appears to engage with. This may partially be due to the nascent state of research into AI and graphic design, as well as the disciplinary methods of computer science.
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Critical and Artistic Dimensions of Graphic Design: A Case Study of Sulki and Min's Practice as Graphic Design Research. The subject and purpose of research in graphic design, or "graphic design research", is often framed under dominant definitions of "graphic design" within the profession. This is generally defined as "the production ...
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It considers the criticisms levelled against graphic design research submitted to the 2014 UK Research Excellence Framework (REF2014). Through analysis of publicly available data, we identify a low volume of graphic design research adhering to traditional academic, non-practice-based forms, and concentrated amongst few institutions.
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This art research database covers a broad range of subjects from fine, decorative and commercial art, to various areas of architecture and architectural design. It features full-text articles, indexing and abstracts for an array of journals, books and more; Coverage back to 1928. Arts & Humanities Citation Index. This link opens in a new window.
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Acta graphica | electronic ACTA GRAPHICA journal publishes scientific research papers, technical papers, reviews, short and preliminary communications, special features and other news from the field of graphical technology, printing and engineering, graphical communication and design, as well as from all basic and applied science fields relevant for graphic technology and arts.
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essay, one "famous" graphic designer, Michael Bierut, advises the neophytes who would follow in his footsteps on techniques for winning ... graphic design research project in which they used a participatory approach to design an HIV/AIDS poster campaign for and with fellow Kenyans. They argue that the participants would have a better sense of
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Online graphical design tools versus conventional designing programs. How visual heuristics assist in segmenting the attention of the viewers. Graphic design and political satire. How graphic design tools have revolutionized the industry. These are some of the top ideas to consider for a thesis topic in this subject.
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Design Writing Research: Writing on Graphic Design. A section on Theory considers the centrality of the written and printed word to post-structuralism and deconstruction. Here, a wide range of design practices are discussed, from the history of punctuation and the origins of international pictograms to the structure of modern typography.
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Graphic Design Masters Theses. Total Papers Total Downloads Downloads in the past year. RISD's graduate program in Graphic Design prepares students for professional practice by emphasizing the roles of social context, media and aesthetics in the production of visible language systems. As a reflection of the discipline itself, the program ...
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A research design is a strategy for answering your research question using empirical data. Creating a research design means making decisions about: Your overall research objectives and approach. Whether you'll rely on primary research or secondary research. Your sampling methods or criteria for selecting subjects. Your data collection methods.
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Written by designers, geared for design students, this guidebook is a valuable resource for better research and writing. It teases the imagination to help find a suitable topic for university level research assignments, embracing both theses and dissertations, and it provides a savvy roadmap for successfully completing all basic elements of the essay product.
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A Report on The History of Graphic Design and Its Important Role in Advertising. 2 pages / 770 words. Thanks to Victor Lardent, graphic designer for British newspaper "The Times," the essay I'm typing is in "Times New Roman. Font design is one of the many aspects of Graphic Design - my passion. As a creatively driven person, graphic ...
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Sustainability
Machine learning (ML) and deep learning (DL) have become very popular in the research community for addressing complex issues in intelligent transportation. This has resulted in many scientific papers being published across various transportation topics over the past decade. This paper conducts a systematic review of the intelligent transportation literature using a scientometric analysis ...

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