Keyboard Shortcuts Research Articles

A Novel Control System for a Laptop with Gestures Recognition

An important lesson learned during the pandemic is that the devices utilized by many people (vending machines, elevators, etc.) can spread the virus and take advantage of contactless programs that can be enabled through gesture recognition. It's a major enabler of smart living and human-computer interaction. It is widely used in controlling equipments. This research presents a novel vision-based real-time gesture recognition system for controlling a laptop. It's a comprehensive system that can do all the required functions needed to remotely control a laptop through hand gesture recognition rather than employing a mouse or keyboard. This system allows changing the position of the mouse point, performing left-click, right-click, double-click, and scrolling up and down. It also provides all the keyboard shortcuts, Print Screen (PrtScr), and Backspace. Furthermore, it allows shutting down as well as creating files and folders. Additionally, it allows playing, muting, pausing media playback, reducing/increasing the brightness, and turning the volume down/up. Moreover, it allows advancing to the next and previous page of the slideshow, as well as zooming in/out. Finally, the system allows gestures to open the most frequently used applications based on the user's choice. In comparison to the previous work, this system is considered unique in that it performs all the functions needed to remotely control the laptop. Previous systems only offer a subset of the tools provided by this proposed system Additionally, it is unique because the user operates all functions solely through gestures, without the need for additional methods.

Virtual Desktop Assistant for Linux

A desktop assistant on Linux is a software application designed to assist users in performing various tasks on their Linux- based desktop system. It typically integrates with the desktop environment and offers a user-friendly interface for performing common tasks such as launching applications, managing files and folders, and accessing system settings. The assistant can also be customized with plugins or extensions to add additional functionality. The main goal of a desktop assistant on Linux is to make the user experience as smooth and efficient as possible. By centralizing common tasks and providing an accessible interface, the assistant eliminates the need for users to navigate complex system settings or memorize multiple keyboard shortcuts. This, in turn, makes it easier for users to perform everyday tasks on their Linux-based desktop system, increasing productivity and overall satisfaction with their experience. Keywords— Deep Learning, Machine learning, NLP, Voice Assistant, Linux, Artificial Intelligence, Speech Recognition, LLMs.

Intelligent Voice Mail System

As technology is advancing, people are coming closer to digital life and digital communication. In this modern period, there are many ways to communicate with others through the internet. Common mode of communication among people through internet is Email. A lot of Business and personal information is exchanged over emails in today's time. Some people cannot use these technologies because either they are illiterate or cannot see the screen. Using this system entitled Voice-based Bare Email for Visually Impaired, it will make the email system very easily accessible to visually challenged people and also help society. This application uses text-to-speech and speech-to-text converters so that visually challenged people can operate the system easily. This system reduces the complexity of remembering the characters or information regarding keyboard shortcuts. Every function will be based on simple voice commands so that those people can easily make use of the technology. It also includes various expert systems, natural language processing, machine vision, and speech recognition. To understand and analyze human language such as English by extracting metadata from keywords, emotions, relations, and concepts in Natural Language Processing

A comparative study of disabled people's experiences with the video conferencing tools Zoom, MS Teams, Google Meet and Skype

ABSTRACT The paper presents a comparative mixed methods study of the accessibility and usability for disabled people of four video conferencing tools, Zoom, MS Teams, Google Meet and Skype. Useable responses were obtained from 81 disabled people with diverse characteristics, mainly in the UK, though some groups had low representation. None of the tools was considered fully accessible and useable. Zoom was both the most commonly used and the most frequently preferred (56.1%) tool, with MS Teams second in usage and a trailing second in preferences (15.9%). It was considered to have better captioning, but otherwise to generally be a poor second to Zoom. Skype was the most commonly used before lockdown, but was considered dated and its limited use was mainly social, whereas the other tools were also used in work and education. The results were used to draw up separate lists of recommendations for developers and meeting organisers and hosts, as the study also identified actions for organisers and hosts to improve meeting accessibility. Developer recommendations include several easy to set customisation and user friendly interface features, involving disabled people and specific accessibility features, including compatibility with assistive technology, keyboard shortcuts for all functions and automatically-on high quality captions.

Quick Guide: Programming a Gaming Mouse for PACS to Optimize Radiology Workflow.

The increasing demand for diagnostic imaging has added to the radiologists' workload, highlighting the shortcomings of conventional computer mice. Radiologists grapple with inefficiencies from frequent mouse clicks and keyboard shortcuts required for various PACS functions. These inefficiencies contribute to cognitive strain, errors, and repetitive strain injuries. High-performance gaming mice, known for their precision in the gaming world, offer multiple custom buttons and superior tracking. These features can streamline radiology tasks. Utilizing a gaming mouse tailored for radiology tasks can substantially enhance efficiency. Our guide offers a step-by-step approach to harnessing the gaming mouse's capabilities for radiology tasks, ensuring radiologists can enhance their workflow and minimize injury risks. Although the guide uses a Logitech gaming mouse for demonstration, it is designed to be intuitive, helping users adapt to their unique needs across different modalities, subspecialties, and various radiology viewer software. Importantly, its fundamental concepts are transferrable to other mouse brands or models with similar customization software.

A Universal Keyboard Shortcuts Reminder (and two bonus tips)

This short article will describe an approach that requires remembering just one – yes 1 - single solitary keyboard shortcut, and that will display a custom list of keyboard shortcuts specific to the program or website being used at the time.

Enabling Efficient Web Data-Record Interaction for People with Visual Impairments via Proxy Interfaces

Web data records are usually accompanied by auxiliary webpage segments, such as filters, sort options, search form, and multi-page links, to enhance interaction efficiency and convenience for end users. However, blind and visually impaired (BVI) persons are presently unable to fully exploit the auxiliary segments like their sighted peers, since these segments are scattered all across the screen, and as such assistive technologies used by BVI users, i.e., screen reader and screen magnifier, are not geared for efficient interaction with such scattered content. Specifically, for blind screen reader users, content navigation is predominantly one-dimensional despite the support for skipping content, and therefore navigating to-and-fro between different parts of the webpage is tedious and frustrating. Similarly, low vision screen magnifier users have to continuously pan back-and-forth between different portions of a webpage, given that only a portion of the screen is viewable at any instant due to content enlargement. The extant techniques to overcome inefficient web interaction for BVI users have mostly focused on general web-browsing activities, and as such they provide little to no support for data record-specific interaction activities such as filtering and sorting – activities that are equally important for facilitating quick and easy access to desired data records. To fill this void, we present InSupport, a browser extension that: (i) employs custom machine learning-based algorithms to automatically extract auxiliary segments on any webpage containing data records; and (ii) provides an instantly accessible proxy one-stop interface for easily navigating the extracted auxiliary segments using either basic keyboard shortcuts or mouse actions. Evaluation studies with 14 blind participants and 16 low vision participants showed significant improvement in web usability with InSupport, driven by increased reduction in interaction time and user effort, compared to the state-of-the-art solutions.

Automation of an atomic force microscope via Arduino

The Atomic Force Microscopy is a very versatile technique that allows to characterize surfaces by acquiring topographies with sub-nanometer resolution. This technique often overcomes the problems and capabilities of electron microscopy when characterizing few nanometers thin coatings over solid substrates. They are expensive, in the half million dollar range for standard units, and therefore it is often difficult to upgrade to new units with improved characteristics. One of these improvements, motorization and automation of the measurements is very interesting to sample different parts of a substrate in an unattended way. Here we report a low cost upgrade under 60 $ to a Dimension 3000 AFM based on a control unit using an Arduino Leonardo. It enables to acquire dozens or hundreds of images automatically by mimicking keyboard shortcuts and interfacing the AFM PCI card.

PENGEMBANGAN ALAT BANTU PENGEDITAN VIDEO DAN MULTIMEDIA BERBASIS ARDUINO USB MIDI

The extensive use of multimedia technology in the film and television industry has greatly enhanced the aesthetics and artistry of film and television works, thereby fundamentally driving the development of the film and television industry. This development of needs in video and multimedia directly impacts the needs in the video editing process. Therefore, in the big video era, changes in the way video is used in various media including social media have had a big impact on editing video content. In speeding up the performance of video and multimedia editing, a shortcut method is needed, usually using a keyboard shortcut. keyboard shortcuts are obviously very helpful in the editing process but despite the fact that it usually takes half the time to issue commands to a computer application using those keyboard shortcuts, most people issue certain commands by clicking on icons on a toolbar or by selecting commands from a pull-down menu. In this study, a tool was designed by utilizing an Arduino microcontroller in the form of a midi controller which makes it easier to access shortcuts to help speed up the process of editing video and multimedia content.

Optimizing radiologist productivity and efficiency: Work smarter, not harder

Radiologists’ personal productivity and efficiency are critically important for both improving patient outcomes and protecting clinician well-being. There are several solutions that individuals can implement to improve personal productivity and efficiency in the radiology workroom. Strategies include understanding the psychology behind productivity, using personal productivity methodologies to accomplish daily tasks, and learning to modulate stress to optimize performance. Institutional infrastructure requirements include a robust departmental commitment to information technology and informatics, including universal log-in systems, internal websites, and dashboards. The workstation itself can be optimized by utilizing hanging protocols, customized keyboard shortcuts, hotkeys, advanced scripts, gaming mice, and other input devices. Personal devices like smartphones can be harnessed to maximize productivity by using online storage applications and radiology-specific applications to augment knowledge. Reading room layouts must be designed to minimize interruptions and workstations must consider ergonomics to prevent fatigue and strain. High-efficiency teams also need to be created to allow radiologists to delegate non-clinical tasks to reduce administrative burdens. Lastly, continued advances in artificial intelligence including the use of smart report templates will lead to substantial gains in radiologists’ productivity and efficiency.

Typealike

We propose a style of hand postures to trigger commands on a laptop. The key idea is to perform hand-postures while keeping the hands on, beside, or below the keyboard, to align with natural laptop usage. 36 hand-posture variations are explored considering three resting locations, left or right hand, open or closed hand, and three wrist rotation angles. A 30-participant formative study measures posture preferences and generates a dataset of nearly 350K images under different lighting conditions and backgrounds. A deep learning recognizer achieves over 97% accuracy when classifying all 36 postures with 2 additional non-posture classes for typing and non-typing. A second experiment with 20 participants validates the recognizer under real-time usage and compares posture invocation time with keyboard shortcuts. Results find low error rates and fast formation time, indicating postures are close to current typing and pointing postures. Finally, practical use case demonstrations are presented, and further extensions discussed.

WoZ4U: An Open-Source Wizard-of-Oz Interface for Easy, Efficient and Robust HRI Experiments.

Wizard-of-Oz experiments play a vital role in Human-Robot Interaction (HRI), as they allow for quick and simple hypothesis testing. Still, a publicly available general tool to conduct such experiments is currently not available in the research community, and researchers often develop and implement their own tools, customized for each individual experiment. Besides being inefficient in terms of programming efforts, this also makes it harder for non-technical researchers to conduct Wizard-of-Oz experiments. In this paper, we present a general and easy-to-use tool for the Pepper robot, one of the most commonly used robots in this context. While we provide the concrete interface for Pepper robots only, the system architecture is independent of the type of robot and can be adapted for other robots. A configuration file, which saves experiment-specific parameters, enables a quick setup for reproducible and repeatable Wizard-of-Oz experiments. A central server provides a graphical interface via a browser while handling the mapping of user input to actions on the robot. In our interface, keyboard shortcuts may be assigned to phrases, gestures, and composite behaviors to simplify and speed up control of the robot. The interface is lightweight and independent of the operating system. Our initial tests confirm that the system is functional, flexible, and easy to use. The interface, including source code, is made commonly available, and we hope that it will be useful for researchers with any background who want to conduct HRI experiments.

E-Mail Reader for Blind People

To develop a voice primarily based email system that will facilitate visually impaired individuals to access email in a problem free manner. Together with providing usage of mail services simply and with efficiency, the system also will cut back the psychological feature work that must be unremarkably taken by the visually impaired to recollect and sort characters using the normal Braille keyboards, which are accessible to them. The graphical user interface of this method has been evaluated against the interface of the traditionally accessible mail system. Not only for visually impaired, but also for people who are illiterate might have the benefit of this technique. The foremost crucial facet which will be thought of developing this technique is that the users of this technique does not have any basic information regarding the keyboard shortcuts used or wherever the keys are used for. All functions to be utilized in this technique are supposed to be easy mouse click operations creating the system very user friendly. This application proposes an android application, designed specifically for visually impaired individuals. This application provides a voice primarily based mailing service which provides them to browse and send mail on their own, without any guidance. The users ought to use certain keywords which can perform certain actions for e.g. Read, Send, and Compose Mail, Address Book etc. This EMAIL system is utilized by a visually handicapped person to access mails easily and with efficiency. Therefore reliance of visually impaired on others for his or her own activities associated with mail are often reduced.

Fiji plugins for qualitative image annotations: routine analysis and application to image classification.

Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To illustrate possible use case of the annotations, and facilitate the analysis of the generated annotations, we provide examples of such pipelines, including data-visualization solutions in Fiji and KNIME, as well as a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.

Fiji plugins for qualitative image annotations: routine analysis and application to image classification

Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To illustrate possible use case of the annotations, and facilitate the analysis of the generated annotations, we provide examples of such pipelines, including data-visualization solutions in Fiji and KNIME, as well as a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.

Eliciting Sketched Expressions of Command Intentions in an IDE

Software engineers routinely use sketches (informal, ad-hoc drawings) to visualize and communicate complex ideas for colleagues or themselves. We hypothesize that sketching could also be used as a novel interaction modality in integrated software development environments (IDEs), allowing developers to express desired source code manipulations by sketching right on top of the IDE, rather than remembering keyboard shortcuts or using a mouse to navigate menus and dialogs. For an initial assessment of the viability of this idea, we conducted an elicitation study that prompted software developers to express a number of common IDE commands through sketches. For many of our task prompts, we observed considerable agreement in how developers would express the respective commands through sketches, suggesting that further research on a more formal sketch-based visual command language for IDEs would be worthwhile.

Fiji plugins for qualitative image annotations: routine analysis and application to image classification

Quantitative measurements and qualitative description of scientific images are both important to describe the complexity of digital image data. While various software solutions for quantitative measurements in images exist, there is a lack of simple tools for the qualitative description of images in common user-oriented image analysis software. To address this issue, we developed a set of Fiji plugins that facilitate the systematic manual annotation of images or image-regions. From a list of user-defined keywords, these plugins generate an easy-to-use graphical interface with buttons or checkboxes for the assignment of single or multiple pre-defined categories to full images or individual regions of interest. In addition to qualitative annotations, any quantitative measurement from the standard Fiji options can also be automatically reported. Besides the interactive user interface, keyboard shortcuts are available to speed-up the annotation process for larger datasets. The annotations are reported in a Fiji result table that can be exported as a pre-formatted csv file, for further analysis with common spreadsheet software or custom automated pipelines. To facilitate and spread the usage of analysis tools, we provide examples of such pipelines, including a complete workflow for training and application of a deep learning model for image classification in KNIME. Ultimately, the plugins enable standardized routine sample evaluation, classification, or ground-truth category annotation of any digital image data compatible with Fiji.

ITOC: Enabling Efficient Non-Visual Interaction with Long Web Documents.

Interacting with long web documents such as wiktionaries, manuals, tutorials, blogs, novels, etc., is easy for sighted users, as they can leverage convenient pointing devices such as a mouse/touchpad to quickly access the desired content either via scrolling with visual scanning or clicking hyperlinks in the available Table of Contents (TOC). Blind users on the other hand are unable to use these pointing devices, and therefore can only rely on keyboard-based screen reader assistive technology that lets them serially navigate and listen to the page content using keyboard shortcuts. As a consequence, interacting with long web documents with just screen readers, is often an arduous and tedious experience for the blind users. To bridge the usability divide between how sighted and blind users interact with web documents, in this paper, we present iTOC, a browser extension that automatically identifies and extracts TOC hyperlinks from the web documents, and then facilitates on-demand instant screen-reader access to the TOC from anywhere in the website. This way, blind users need not manually search for the desired content by moving the screen-reader focus sequentially all over the webpage; instead they can simply access the TOC from anywhere using iTOC, and then select the desired hyperlink which will automatically move the focus to the corresponding content in the document. A user study with 15 blind participants showed that with iTOC, both the access time and user effort (number of user input actions) were significantly lowered by as much as 42.73% and 57.9%, respectively, compared to that with another state-of-the-art solution for improving web usability.

Shortcut Gestures for Mobile Text Editing on Fully Touch Sensitive Smartphones

While advances in mobile text entry enable smartphone users to type almost as fast as on hardware keyboards, text-heavy activities are still not widely adopted. One reason is the lack of shortcut mechanisms. In this article, we determine shortcuts for text-heavy activities, elicit shortcut gestures, implement them for a fully touch-sensitive smartphone, and conduct an evaluation with potential users. We found that experts perform around 800 keyboard shortcuts per day, which are not available on smartphones. Interviews revealed the lack of shortcuts as a major limitation that prevents mobile text editing. Therefore, we elicited gestures for the 22 most important shortcuts for smartphones that are touch-sensitive on the whole device surface. We implemented the gestures for a fully touch-sensitive smartphone using deep learning and evaluated them in realistic scenarios to gather feedback. We show that the developed prototype is perceived as intuitive and faster than recent commercial approaches.

Semi-automated transcription and scoring of autobiographical memory narratives.

Autobiographical memory studies conducted with narrative methods are onerous, requiring significant resources in time and labor. We have created a semi-automated process that allows autobiographical transcribing and scoring methods to be streamlined. Our paper focuses on the Autobiographical Interview (AI; Levine, Svoboda, Hay, Winocur, & Moscovitch, Psychology and Aging, 17, 677-89, 2002), but this method can be adapted for other narrative protocols. Specifically, here we lay out a procedure that guides researchers through the four main phases of the autobiographical narrative pipeline: (1) data collection, (2) transcribing, (3) scoring, and (4) analysis. First, we provide recommendations for incorporating transcription software to augment human transcribing. We then introduce an electronic scoring procedure for tagging narratives for scoring that incorporates the traditional AI scoring method with basic keyboard shortcuts in Microsoft Word. Finally, we provide a Python script that can be used to automate counting of scored transcripts. This method accelerates the time it takes to conduct a narrative study and reduces the opportunity for error in narrative quantification. Available open access on GitHub ( https://github.com/cMadan/scoreAI ), our pipeline makes narrative methods more accessible for future research.