Text Font Research Articles

Exploring fonts as retrieval cues in text-based learning

A growing body of research focuses on optimizing retrieval processes to help learners recall information from memory. The context-dependent memory effect suggests that information retrieval is more effective when the retrieval context matches the learning context. This phenomenon has been investigated in a variety of study materials and samples. However, there is a research gap in which this effect has not yet been investigated with font. Therefore, the font may act as a contextual retrieval cue, making it easier for learners to recall the presented information. In this context, the present experiment assumes that a match between the font used during learning (encoding phase) and that used during testing (decoding phase) improves retrieval processes and thus learning performance, while a mismatch has a negative effect. To test this assumption, 130 university students were randomly assigned to one condition of a two (font of learning texts: Haettenschweiler vs. Times New Roman) × two (font of learning questions: Haettenschweiler vs. Times New Roman) between-subjects design. Contrary to expectations, using the same font for encoding and decoding did not improve learning performance. Furthermore, learners did not report higher levels of mental effort when they had to work on learning questions presented in the same font as the learning texts. Although the font of the learning text is the most salient feature, it does not seem to serve as an effective retrieval cue in text-based learning.

Optimizing Mobile Reading Experience: Adaptive Font Size Adjustment in a Context-Aware Application

The reading experience on a mobile device can be influenced by many external elements that affect the viewing conditions. The user holding position, operating style, and the light conditions of the surroundings can all play a crucial factor in the legibility of the text. Furthermore, the user’s eye conditions may be an extra factor to consider when determining how to improve the reading experience. This study presents a context-aware application that adjusts the text font size based on the distance between the user and the device. The users select their preferred font size at certain distances in the calibration phase, accounting for individual preferences or their eye conditions, and the application uses the device’s front camera to calculate the distance in real time and adjust the font size accordingly. We present implementation details and challenges faced during development and how they were addressed. A two-part experiment ([Formula: see text] = 34) revealed that the application scored an excellent usability score while no differences were found between users with and without eye conditions, showing that both user groups find it equally usable. Additionally, initial results suggest that the visual landmarks used showed a promising start at addressing issues related to our approach.

Pelatihan Aplikasi Mendeley Kepada Mahasiswa Tingkat Akhir Universitas Amikom Purwokerto

When writing final assignments or theses, many students still have difficulty processing existing citations, this is also experienced by students at Amikom University, Purwokerto. Mistakes in taking citations such as text that does not match the thesis guidelines, text fonts and spacing are not paid attention to even though you have used tools such as using applications for citations. When the student's report was checked by the supervisor, there was still a note of improvement. When reports are submitted to the library, the reports will also be checked again to see whether they comply with the library format. The majority of student reports are returned by the library for correction. This also applies when students make journals, there are still many errors in writing citations. The aim of the training is to reduce student errors in taking citations. The activity implementation method consists of the preparation stage, implementation stage and evaluation stage. The result of this training is a reduction in student errors in citing scientific articles, books and so on.

Penerapan Algoritma Backpropagation Untuk Text Recognition Yang Ditranslate Ke Bahasa Daerah

Every area of the community there is information, news, announcements or notifications through print media such as pictures, banners, posters and paper. However, there are many foreign languages (English) in the information which makes people not understand the language, because people only understand their own regional language (Sundanese) and the lack of media to help people understand the regional language (Sundanese) to a foreign language (English). Therefore, the author takes research on android-based text detection. Text detection or called Optical Character Recognition (OCR) is a system that can detect text into data files that can be processed in such a way. The method of collecting data or information in this study uses qualitative, the method for developing this system uses the waterfall method which has the advantage of being able to accelerate system development and using a backpropagation algorithm for text recognition. Backpropagation algorithm is an algorithm that can minimize errors, so as to make text detection more accurate. The results of the text detection accuracy are 97% and the error accuracy results are 3%, the text accuracy results are taken from a total of 14 samples, and 68 words. The results of text detection are affected by several cases such as the type of text font, the level of light in the image and the direction in which the photo or image is taken.

Efficient and accurate reader, meaning, and recommendation systems for blind persons

Many systems are available to help the blind person in his life. This paper aims to prove the specific proposed audio reading, meaning, and recommendation system are efficient and real-time for the blind person. These systems are tested and discussed from the aspects of real-time, efficiency, accuracy, and reliability. The dataset is images with different text font sizes and views which is used in testing these three systems.

Design Principles for VanVR APP: a Virtual Anatomy Lab

The VanVR APP (Vancouver Virtual Reality Anatomy and Pathology Project) is a virtual anatomy lab with 3D anatomy dissection scans, which in the post‐pandemic learning environment is a “digital twin” to the physical lab. The principles of this re‐design are based on instructors' need to offer an alternate supplemental teaching environment, and students’ need to access high‐quality anatomy scans preparing for the dissection lab experience.VanVR was created using Unity and WebGL offering two separate user interfaces (UI): one for students and one for instructors. The student UI leads to a virtual anatomy lab (VAL) of interactive 3D models. The instructor UI; the Lab Maker (LM), allows instructors to customize their courses from a wide database of fully‐labeled specimens, images, and videos. VanVR’s user experience (UX) of the VAL was designed to mimic a lab’s environment including anatomy code of conduct and many control functions. UI and UX designs intend to meet student needs with a focus on intuitive interfaces and interactions to maximize attention on the anatomy content rather than navigating technological difficulties.VanVR was designed as an accessible web app using a traditional and universal design layout that allows for seamless future mobile/tablet expansion. In the student portal and the LM, organized by importance, the main bulk of the course material was centrally placed in common sections to allow for an effective tree hierarchy and smooth accessibility. The student UI visual hierarchy was highlighted via a checklist to track weekly learning progress supplemented by course material, lab manuals, specimens, videos, and images. The login information, content menu, and sub‐menus were then distributed around the main grid. This layout helped to convey easy navigation, accessibility, and uniform connectivity. The anatomy content menu was sorted by body regions (atlas or textbook hierarchy). The aim of VanVR's layout was to mimic familiar apps for a smooth user experience. Moreover, to attain user seamless transition, VanVR’s layout matched UBC’s learning management system; Canvas features such as student checklists, content upload, and editing course material in the LM.Equal principles were used in the UX, the VAL design resembles an actual anatomy lab, this mimicry principle induces learnability. The user control shows the main elements in a simple hierarchy, design, colors, and text font granting intuitive and seamless navigation. To deliver flexibility and redundancy, we added multiple logical routes to finish tasks and bypass system lags. For more student‐instructor interaction, instructors were given the feature to control the number of labels on the specimens or pose question labels to match the learning objectives. As a result, VanVR UI and UX design followed basic aesthetics aiming for an efficient and accessible learning/teaching tool.Our future plan includes adapting the UI and UX to smartphone/tablet screen size and features. For more accessibility and redundancy, a search feature will be added to allow users to rapidly find specimens.

An Adaptive Deep Learning Framework for Fast Recognition of Integrated Circuit Markings

Fast recognition of integrated circuit (IC) markings is an essential but challenging task in electronic device manufacturing lines. This article develops an adaptive deep learning framework to facilitate the fast marking recognition of IC chips. The proposed framework contains four deep learning components, namely, chip segmentation, orientation correction, character extraction, and character recognition. The four components utilize different convolutional neural network structures to guarantee excellent adaptivity to a wide range of IC types and mitigate the influence of the low-quality chip images. In particular, the character extraction model is comprised of two improved label generation strategies and a proposed border correction method, so as to accommodate tiny scale chips and compactly printed markings. Experiments from the chip image dataset of a real laptop manufacturing line reached a recognition Precision of 91.73% and the Recall of 92.93%. The results demonstrate the superiority of the proposed framework to the state-of-the-art models and the effectiveness of handling a great diversity of chips with different scales, shapes, text fonts, marking colors, and layouts.

Arbitrary Font Generation by Encoder Learning of Disentangled Features.

Making a new font requires graphical designs for all base characters, and this designing process consumes lots of time and human resources. Especially for languages including a large number of combinations of consonants and vowels, it is a heavy burden to design all such combinations independently. Automatic font generation methods have been proposed to reduce this labor-intensive design problem. Most of the methods are GAN-based approaches, and they are limited to generate the trained fonts. In some previous methods, they used two encoders, one for content, the other for style, but their disentanglement of content and style is not sufficiently effective in generating arbitrary fonts. Arbitrary font generation is a challenging task because learning text and font design separately from given font images is very difficult, where the font images have both text content and font style in each image. In this paper, we propose a new automatic font generation method to solve this disentanglement problem. First, we use two stacked inputs, i.e., images with the same text but different font style as content input and images with the same font style but different text as style input. Second, we propose new consistency losses that force any combination of encoded features of the stacked inputs to have the same values. In our experiments, we proved that our method can extract consistent features of text contents and font styles by separating content and style encoders and this works well for generating unseen font design from a small number of reference font images that are human-designed. Comparing to the previous methods, the font designs generated with our method showed better quality both qualitatively and quantitatively than those with the previous methods for Korean, Chinese, and English characters. e.g., 17.84 lower FID in unseen font compared to other methods.

Resume Screening and Recommendation System using Machine Learning Approaches

Candidates apply in large numbers for jobs on web portals by uploading their resumes, due to the rapid growth of online-based recruitment systems. On the other hand, the resume has its formatting style, data blocks, and segments, as well as a variety of data formatting options such as text alignment, color, font type, and font size, making it an excellent example of unstructured data. As a result, filtering applicants for the appropriate position in an organization becomes a difficult task for recruiters. We can use Natural Language Processing (NLP) techniques to extract the relevant information from the resume to save time and effort. Also, a Machine Learning (ML) model is trained to check whether a candidate’s skills, experiences, and other aspects are suitable for that particular role. In addition to that, our system will also recommend the other available job roles based on the candidate’s skillset.

Effects of Font Style and Font Color in News Text on User Cognitive Load in Intelligent User Interfaces

The advances on the Internet and news media technologies suggest intelligent and personalised media interfaces in order to improve reading efficiency of news readers and enhance news disseminations. Cognitive load is one of factors that affect the understanding ability of news readers and therefore news dissemination. It is expected that the display elements in an intelligent user interface of news media could be automatically adjusted to modulate the audience’s perceived cognitive load level in order to improve the news reading efficiency. While the font style and font colour of news text are the main display elements in the user interface of news media, it is not clear how these elements affect perceived cognitive load of news readers. This paper investigates perceived cognitive load of news readers under different font style and font colour conditions. Experiments with the news text in Chinese as a case study found that the change of text font style of keywords resulted in the increase of the reader’s perceived cognitive load during reading news text under the low introduced cognitive load and blue colour displayed keywords. While under the high introduced cognitive load, the italic font and red colour of keywords text resulted in the decrease of the reader’s perceived cognitive load significantly during reading news text, which therefore improves the news reading efficiency. This paper is limited to the effects of two aspects of news text (font styles and colours) on user’s perceived cognitive load. The future work will focus on the investigation of effects of other factors such as news pictures and their colours, numbers, and locations on user’s perceived cognitive load.

An Investigation of Critical Thinking Skills in Illustrated Children's Books

Purpose: The purpose of this research is to investigate the critical thinking skills in illustrated children's books in pre-school education classes.Design/Methodology/Approach: Within the scope of the research, 200 picture children's books were analyzed by document analysis method.Findings: According to the findings, it was observed that in the analyzed children's books, there were more phrases that support critical thinking skills such as inference, evaluation and self-regulation while high-level skills such as analysis and interpretation were rather limited. In addition, while phrases supporting the explanation skills were included directly in the examined children's books, it was observed that there was no indirect mention.As a result, research findings showed that critical thinking skills are limited in the illustrated children's books, and they are usually given directly. These results also clearly revealed the existence of a didactic approach, an attitude that restricts critical thinking in children's books. Illustrated children’s books prepared for early childhood should avoid this approach and they should be enriched with content that supports children's thinking skills.Highlights: The abstract of the article should be written by adding the "Calibri (Body)" text font, 8 font size, single line spacing and 6 nk space at the end of the paragraph. The abstract should be between 150 and 350 words. In the abstract, the purpose of the article, the method used, the main findings, conclusions and suggestions should be clearly stated.

USE OF TOOLS AND SERVICES OF CLOUD-BASED SYSTEMS IN TEACHERS’ TRAINING AND PROFESSIONAL DEVELOPMENT: ASPECT OF AUGMENTED REALITY

The article reveals the aspect of using augmented reality (AR) as a means of a cloud-based open education and science system. Research methods: analysis, generalization, systematization of scientific-methodical sources on the research problem, analysis of cloud-based tools and services, determination of theoretical bases of teacher professional development on using cloud-oriented systems of open education and science. In the context of open science, the interest of scientists in the use of ICT during the period of the large-scale COVID-19 pandemic was analyzed and it was found that the number of publications in the areas of use of information and communication technologies, the introduction of distance learning, the development of information and communication and STEM competence has increased rapidly. The survey of lyceums teachers resulted that teachers chose three simple means for organizing distance learning, as well as the direct dependence in the choice of these means – digital analogs of full-time education (Zoom – lesson, Viber – diary, website – school announcements). The author considered the issue of the lack of high-quality digital content and the use of AR-objects, implemented using the MERGE Cube technology, in pedagogical practice. The cloud-based system of using MERGE Cube for learning is described, the stages of using MERGE Cube in the educational process, the criteria for the quality of AR-content (correspondence of virtual additions to the content of the lesson or the topic being studied; sound effects emphasize artistic or other meaning; video fragments demonstrate processes, events or video instructions by content; the process of playing AR objects is simple, intuitive; the process of playing AR is technically stable; the text font is dynamic; 3D images are clear; AR objects are reproduced in various operating systems). The author draws attention to the need to develop instructions and digital maps for the lesson. It was found that the key factor in the spread of AR technology in education is open access to educational content and the development of teachers’ relevant competencies.

Pupil changes in persons aged 8 to 79 during text reading – an eye-tracking study

Summary The Eye Tribe eye-tracker was used to capture pupil sizes and fixation times of 40 people aged 8 to 79 years during text reading. The dependence of the number of readable lines on the participants’ age was determined. A function describing the dependence of the eye surface area on age was also derived. Visual perception of the maximum number of consecutive lines with decreasing text font size is best for people aged 30–40. For the studied age group, the pupil area decreased with age by approximately 300%. An approximately two-fold increase in average fixation times was recorded.

디지털 이미지에 기록된 시간 정보를 추출하기 위한 OCR 기법들에 대한 분석

The time information recorded in a vehicle black box or CCTV is displayed in the text time(ex: YYYY/MM/DD hh:mm:ss). However, when restoring images from inactive areas, temporary files, or damaged video files, there could be a problem that the sequence of images restored to frame units is not arranged in that of the actual recorded time. To resolve this issue, we recognize time information recorded in text format at the top or bottom of the image, and rename the image file via the recognized time information. At that time, images that have been renamed and sorted chronologically can be made into continuous videos. In this paper, Optical Character Recognition(OCR) was used to recognize time information. OCR-related research has continued for a long time and has recently been available through many open sources. Thus, time information of the image is extracted by applying Convolutional Recurrent Neural Network(CRNN) based OCR, Tesseract OCR, and EasyOCR. The expression of time information in vehicle black boxes and CCTV is expressed in various ways(ex: text font, background and text size). The performance of each OCR was compared and analyzed through test images of time information presented in various forms. It was shown from the comparative analysis that the CRNN-based method has the highest recognition performance among OCRs used in the experiment. Moreover, it was confirmed that a prediction rate is approximately 5 times faster for predicting a single image.

The Collected Verse of John, Lord Hervey (1696–1743), ed. Bill Overton, with Elaine Hobby and James McLaverty.

<i>The Collected Verse of John, Lord Hervey (1696–1743)</i>, ed. Bill Overton, with Elaine Hobby and James McLaverty.

A Method of Image Quality Assessment for Text Recognition on Camera-Captured and Projectively Distorted Documents

In this paper, we consider the problem of identity document recognition in images captured with a mobile device camera. A high level of projective distortion leads to poor quality of the restored text images and, hence, to unreliable recognition results. We propose a novel, theoretically based method for estimating the projective distortion level at a restored image point. On this basis, we suggest a new method of binary quality estimation of projectively restored field images. The method analyzes the projective homography only and does not depend on the image size. The text font and height of an evaluated field are assumed to be predefined in the document template. This information is used to estimate the maximum level of distortion acceptable for recognition. The method was tested on a dataset of synthetically distorted field images. Synthetic images were created based on document template images from the publicly available dataset MIDV-2019. In the experiments, the method shows stable predictive values for different strings of one font and height. When used as a pre-recognition rejection method, it demonstrates a positive predictive value of 86.7% and a negative predictive value of 64.1% on the synthetic dataset. A comparison with other geometric quality assessment methods shows the superiority of our approach.

English billboard text recognition using deep learning

English billboards are common in our daily work and life, and how to effectively recognize them is a problem worthy of study. This paper mainly uses Progressive Scale Expansion Network (PSENet) and Convolutional Recurrent Neural Network (CRNN) to conduct text recognition experiments on English billboards. The English billboards are divided into four categories: text distortion, larger background, special text font, and normal format. PSENet is used for text detection, and CRNN is used for text recognition. The identification results of PSENet and CRNN revealed differences among the four groups of English billboards: normal format text recognition is the best, and large background text recognition is the worst, and the recognition effect of text distortion and special text font is less accurate. Finally, the work of this paper is analyzed and summarized, and the future work is prospected.

The Development and Usability Assessment of an mHealth Application to Encourage Self-Care in Pregnant Women against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has caused serious concerns in pregnant women. Self-care mHealth applications can provide helpful guidelines for COVID-19 prevention or management in case of infection. This study aimed to develop and then assess a self-care smartphone-based application to provide self-care for pregnant women against COVID-19. The present study was conducted in two phases. First, a needs assessment was performed based on the opinions of 30 obstetricians and pregnant women. Then, relying on the results, a smartphone-based application was prototyped and assessed in terms of its usability and user satisfaction. To assess the application, 36 pregnant women (11 infected with COVID-19) were asked to use the application for a week. The QUIS questionnaire 5.5 was used for assessment, and the results were analyzed via descriptive statistics in SPSS 23. According to the obstetricians and pregnant women, of the 41 information requirements, 35 data elements were noted to be essential in the needs assessment. Features of the application were placed in four categories of User's Profile, Lifestyle, Disease Management and Control, and Application Functions (e.g., introducing high-risk places in terms of COVID-19 prevalence in each city, introducing specialized COVID-19 medical centers to pregnant women to receive services, medication management, stress management and control, nutrition and diet management, sleep management, contacting physicians, doctor's appointment reminder, searching the available educational materials, and making application adjustments such as text font, size, and color). With an average score of 7.94 (out of 9), pregnant women rated the application at a good level. The application can be used to reduce anxiety and stress about COVID-19 in mothers, provide access to reliable information to answer possible questions, identify high-risk locations, and provide pregnant women with instant access to healthcare facilities and information related to COVID-19 self-care processes.

Website categorization via design attribute learning

Malicious software (malware) is a challenging cybersecurity threat, as it is often bundled with legitimate software and downloaded by naïve users. A significant source of malware downloads is via crack websites that are used to circumvent copyright protection mechanisms. Crack websites often change URLs and IPs to avoid automatic detection; however, in many cases, they preserve specific visual designs that signal the website's function to potential users (such as particular colors, text fonts, shapes, and sizes.). Website design features are numerous, have high dimensionality and complicated interactions, making categorization challenging. This study shows that straightforward machine learning models for categorizing Crack and Malicious websites can considerably benefit from using design features. We report on two experiments based on unbalanced datasets and show that classification by using design features can reach a categorization accuracy of over 90% with an F1-score over 77% in some instances. Finally, we discuss the results in the context of developing intelligent security mechanisms.

The Latest Trends in Graphic Design: Handmade Typographic Posters

Modern art and design movements such as Art Nouveau, Art Deco and international Typographic Style emerged in Switzerland in the 1950s have been a major influence in the development of modern posters language. Today, this contemporary orientations are being developed and dealt with in a different dimension.Typography in posters is used within the image or the typographic elements themselves coming together and converting into a visual form. The failure of the image of the poster to convey the desired message quickly and dramatically, not to observe the spaces in the use of typographic elements, to pass in front of the image with the color of the font used, lack of simplicity may be mentioned as many problems that can be replicated. However typography is not only the gap between characters, text font and color. It is the conformity of letters with the design applied. It is the art of representing the work with letters. And in this representation designers have made different attempts to find the most accurate and newest and were directed to handmade posters in their search.In this research, basis of the problems of the orientation to the hand-crafted typographic posters which is a different quest spreading rapidly today and reasons pushing the designer to this new quest were examined and in the light of obtained findings, examples of typographic posters in new quests made by designers were presented. Keywords: handmade typography, typographic problem in posters, experimental typography.