User's Point Of View Research Articles

Machine learning in microscopy - insights, opportunities and challenges.

Machine learning (ML) is transforming the field of image processing and analysis, from automation of laborious tasks to open-ended exploration of visual patterns. This has striking implications for image-driven life science research, particularly microscopy. In this Review, we focus on the opportunities and challenges associated with applying ML-based pipelines for microscopy datasets from a user point of view. We investigate the significance of different data characteristics - quantity, transferability and content - and how this determines which ML model(s) to use, as well as their output(s). Within the context of cell biological questions and applications, we further discuss ML utility range, namely data curation, exploration, prediction and explanation, and what they entail and translate to in the context of microscopy. Finally, we explore the challenges, common artefacts and risks associated with ML in microscopy. Building on insights from other fields, we propose how these pitfalls might be mitigated for in microscopy.

Evaluating both usability and accessibility: the case of access@tour by action – a digital solution for accessible tourism

Aim: Information systems can help improve accessible tourism conditions. During the development of accessible technology, a crucial phase is testing. Notwithstanding, usability testing methodologies often dismiss accessibility. To overcome this gap, this work contributes with an innovative mixed-method testing methodology that integrates accessibility and usability components in technology evaluation. The capabilities of this methodological process are demonstrated through testing the prototype of a mobile solution for accessible tourism – access@tour by action. Methods: Nine experts evaluated the platform and helped correct accessibility failures. Afterward, 78 end-users tested the prototype. The procedure includes a set of tasks to be performed in the prototype and a final questionnaire. This questionnaire was specifically created for accessibility markets and is itself a significant contribution. Results: Testing with experts helped improve the prototype’s accessibility before it reached end-users. The results with end-users are provided in two distinct ways. First, the task performance measures are presented, which showed overall good completion rates. Second, the results obtained from the questionnaires are disclosed. Overall, the platform was considered relevant, accessible, and easy to use. Still, some minor flaws were identified regarding interface connectivity, symbology, and reading sequence. Thus, improvements are suggested based on obtained feedback. Conclusion: The testing procedure was essential to gather input from a user point of view, ensuring the final version of the access@tour by action is accessible and, therefore, “usable”. This allowed for validating the methodological method, significantly contributing to future research on evaluating technology accessibility.

Input currents of CMOS SAR ADC in microcontroller, their measurement and behavior model from users point of view

The article introduces the possible issue of internal CMOS Successive Approximation Register microcontroller’s Analog-to-Digital Converters (ADC) input currents. It describes the nature of the ADC input current and its dependence on the sampling frequency but also explains the issue when the ADC input appears to the user as a voltage source. Methods for measurement of parameters such as input charge, residual voltage, and equivalent capacitance of sample-hold circuits are presented and used in the proposed simplified model of ADC input behavior. These parameters, which are not listed in the datasheets, if not respected in the data acquisition design, can adversely affect how the ADC is used when measuring signal sources with non-negligible internal resistance. The article also explains how to solve a voltage measurement on a source with high internal resistance even in a situation where, according to datasheets, it should already have limitations. If the microcontroller contains a dynamically switched multiplexer, it can lead to other consequences, such as changing the input current or residual voltage. The proposed simplified CMOS SAR ADC input behavior model in an MCU can help users in an MCU-based data acquisition system design.

Devanagari CAPTCHA: For the Security in Web

Completely Automated Public Turing Test to Tell Computers and Humans Apart or CAPTCHA is a solution for cyber-attack. CAPTCHA is a small challenge that an internet user has to pass before accessing any online service. The most common type of CAPTCHA is text-based CAPTCHA, in which a small image (contains a random number of alphabets) is presented before the user. The user has to identify and then type the alphabet in a text box. The textual information in the CAPTCHA must not be identified by a bot (computer code). So, artificial noise and distortion are applied in the image. Earlier text-based schemes use English alphabets, but over time non-English language-based text CAPTCHAs also came into the picture. Native language-based text CAPTCHA is very useful for internet users who do not know the English language. This article is an effort towards the current status of the Devanagari script-based CAPTCHAs. We have analyzed 28 unique Devanagari CAPTCHAs from a security and usability point of view. Total 28000 different samples are collected for this experiment. For the success of a text-based CAPTCHA, it must be very secure from the bot and easy for human beings. Devanagari CAPTCHA can be very beneficial for Indian websites. This paper is written by keeping the importance of Devanagari script-based CAPTCHA.

DIGITAL EARTH OBSERVATION INFRASTRUCTURES AND INITIATIVES: A REVIEW FRAMEWORK BASED ON OPEN PRINCIPLES

Abstract. Recent years have seen a tremendous increase of digital Earth Observation (EO) infrastructures, which provide web-based environments for accessing and processing data in a highly automated and scalable way. However, the current landscape of EO infrastructures and initiatives is fragmented, with various levels of user on-boarding and uptake success. The current work aims to make sense of this complex landscape by providing two main contributions. First, it offers a classification scheme used to review and analyse more than 150 EO infrastructures and initiatives. Then, adopting a user-centric perspective, the main limitations and obstacles currently faced by users when working with the existing EO platforms are identified. For each of these limitations, we propose a number of good practices that could benefit, from a user point of view, the design and functioning of EO platforms. Some technological enablers, i.e. specific resources (such as software components, standards and data encodings) that emerged from the analysis as holding a great potential for improving the usability of existing EO platforms, are finally listed. The work aims to provide a first scientific insight on how to best design and operate EO platforms to maximise the benefits of their user communities.

Usability Evaluation of Mobile USSD-SMS Interactive Result Checking System for Resource-Constrained Settings (MIRCS) using System Usability Score (SUS).

Mobile phones, especially smartphones have impacted the way we access information related to education. For instance, students are now able to view their results using a smartphone on a browser. However, these result systems that make it possible for students to view their exam results through web browsers or emails on their mobile devices need an internet connection for the process to work as expected. Also, given the indigent nature of most students in developing countries, this creates a digital divide for students that do not own smartphones. With many students coming from rural and often low economic status homes, not many can afford smartphones. Hence, leveraging on the potentials of Unstructured Supplementary Service Data (USSD) and Short Message Service (SMS), a Mobile USSD-SMS Interactive Result Checking System for Resource-Constrained Settings (MIRCS) was developed to provide a device agnostic accessible Result Checking System. This study evaluated MIRCS using System Usability Scale (SUS) to verify the effectiveness from a usability point of view. The result of the evaluation shows that the MIRCS is usable which received grade C (66.21), although it does not meet the acceptable level specified by SUS. Further analysis of the interaction with respondents suggests some areas of improvement to include cost of service, high availability and accuracy.

A simple single-cycle interactive strategy to improve deep learning-based segmentation of organs-at-risk in head-and-neck cancer.

Interactive segmentation seeks to incorporate human knowledge into segmentation models and thereby reducing the total amount of editing of auto-segmentations. By performing only interactions which provide new information, segmentation performance may increase cost-effectively. The aim of this study was to develop, evaluate and test feasibility of a deep learning-based single-cycle interactive segmentation model with the input being computer tomography (CT) and a small amount of information rich contours. A single-cycle interactive segmentation model, which took CT and the most cranial and caudal contour slices for each of 16 organs-at-risk for head-and-neck cancer as input, was developed. A CT-only model served as control. The models were evaluated with Dice similarity coefficient, Hausdorff Distance 95th percentile and average symmetric surface distance. A subset of 8 organs-at-risk were selected for a feasibility test. In this, a designated radiation oncologist used both single-cycle interactive segmentation and atlas-based auto-contouring for three cases. Contouring time and added path length were recorded. The medians of Dice coefficients increased with single-cycle interactive segmentation in the range of 0.004 (Brain)-0.90 (EyeBack_merged) when compared to CT-only. In the feasibility test, contouring time and added path length were reduced for all three cases as compared to editing atlas-based auto-segmentations. Single-cycle interactive segmentation improved segmentation metrics when compared to the CT-only model and was clinically feasible from a technical and usability point of view. The study suggests that it may be cost-effective to add a small amount of contouring input to deep learning-based segmentation models.

Development of DVS evaluation methods from user perspective

We report measurement methods and metrics for the evaluation of dynamic vision sensor (DVS) pixels. In particular, we developed automated test environments and test metrics which can quantify the sensitivity, latency and background noise of DVS pixels. For sensitivity measurements, response probabilities of pixels were analyzed at various conditions, such as base light intensity and region of interests of a sensor. Pixel latency was measured by varying the duty of light pulse, and noise level were also characterized at different light intensities. We expect the developed methods and metrics can help to clarify the performance of DVS pixels at the user point of view.

Perceptions of a Secure Cloud-Based Solution for Data Sharing During Acute Stroke Care: Qualitative Interview Study

Acute stroke care demands fast procedures performed through the collaboration of multiple professionals across multiple organizations. Cloud computing and the wide adoption of electronic medical records (EMRs) enable health care systems to improve data availability and facilitate sharing among professionals. However, designing a secure and privacy-preserving EMR cloud-based application is challenging because it must dynamically control the access to the patient's EMR according to the needs for data during treatment. We developed a prototype of a secure EMR cloud-based application. The application explores the security features offered by the eHealth cloud-based framework created by the Advanced Secure Cloud Encrypted Platform for Internationally Orchestrated Solutions in Health Care Horizon 2020 project. This study aimed to collect impressions, challenges, and improvements for the prototype when applied to the use case of secure data sharing among acute care teams during emergency treatment in the Netherlands. We conducted 14 semistructured interviews with medical professionals with 4 prominent roles in acute care: emergency call centers, ambulance services, emergency hospitals, and general practitioner clinics. We used in-depth interviews to capture their perspectives about the application's design and functions and its use in a simulated acute care event. We used thematic analysis of interview transcripts. Participants were recruited until the collected data reached thematic saturation. The participants' perceptions and feedback are presented as 5 themes identified from the interviews: current challenges (theme 1), quality of the shared EMR data (theme 2), integrity and auditability of the EMR data (theme 3), usefulness and functionality of the application (theme 4), and trust and acceptance of the technology (theme 5). The results reinforced the current challenges in patient data sharing during acute stroke care. Moreover, from the user point of view, we expressed the challenges of adopting the Advanced Secure Cloud Encrypted Platform for Internationally Orchestrated Solutions in Health Care Acute Stroke Care application in a real scenario and provided suggestions for improving the proposed technology's acceptability. This study has endorsed a system that supports data sharing among acute care professionals with efficiency, but without compromising the security and privacy of the patient. This explorative study identified several significant barriers to and improvement opportunities for the future acceptance and adoption of the proposed system. Moreover, the study results highlight that the desired digital transformation should consider integrating the already existing systems instead of requesting migration to a new centralized system.

Risk Assessment System of Fall in the Elderly Using Artificial Intelligence and Cloud Computing

This paper presents a Cloud-based online tool for helping health professionals to predict the risk of falling in the elderly by using the well-known Tinetti’s Test. This tool implements a Deep Learning-based method for allowing several Tinetti scale’s items to be automatically estimated, simply using a conventional camera or a recorded video. From these sources of information, patients’ skeleton is recognized and their movements analyzed by applying some geometric calculations, which provide an objective risk assessment. Results are represented as a set of plots easily interpretable by experts. Several tests, in a controlled environment, have been carried out to validate the accuracy and reliability of the system. Moreover, some tests have been also made with real elderly patients, whose results have been evaluated by therapists. The benefits of using such remote tool for assessing (objective) fall risk, from a usability point of view, are also highlighted.

A methodology for assessing computation/communication overlap of MPI nonblocking collectives

A methodology for assessing computation/communication overlap of MPI nonblocking collectives

The eWaterCycle platform for open and FAIR hydrological collaboration

Abstract. Hutton et al. (2016) argued that computational hydrology can only be a proper science if the hydrological community makes sure that hydrological model studies are executed and presented in a reproducible manner. Hut, Drost and van de Giesen replied that to achieve this hydrologists should not “re-invent the water wheel” but rather use existing technology from other fields (such as containers and ESMValTool) and open interfaces (such as the Basic Model Interface, BMI) to do their computational science (Hut et al., 2017). With this paper and the associated release of the eWaterCycle platform and software package (available on Zenodo: https://doi.org/10.5281/zenodo.5119389, Verhoeven et al., 2022), we are putting our money where our mouth is and providing the hydrological community with a “FAIR by design” (FAIR meaning findable, accessible, interoperable, and reproducible) platform to do science. The eWaterCycle platform separates the experiments done on the model from the model code. In eWaterCycle, hydrological models are accessed through a common interface (BMI) in Python and run inside of software containers. In this way all models are accessed in a similar manner facilitating easy switching of models, model comparison and model coupling. Currently the following models and model suites are available through eWaterCycle: PCR-GLOBWB 2.0, wflow, Hype, LISFLOOD, MARRMoT, and WALRUS While these models are written in different programming languages they can all be run and interacted with from the Jupyter notebook environment within eWaterCycle. Furthermore, the pre-processing of input data for these models has been streamlined by making use of ESMValTool. Forcing for the models available in eWaterCycle from well-known datasets such as ERA5 can be generated with a single line of code. To illustrate the type of research that eWaterCycle facilitates, this paper includes five case studies: from a simple “hello world” where only a hydrograph is generated to a complex coupling of models in different languages. In this paper we stipulate the design choices made in building eWaterCycle and provide all the technical details to understand and work with the platform. For system administrators who want to install eWaterCycle on their infrastructure we offer a separate installation guide. For computational hydrologists that want to work with eWaterCycle we also provide a video explaining the platform from a user point of view (https://youtu.be/eE75dtIJ1lk, last access: 28 June 2022)​​​​​​​. With the eWaterCycle platform we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both Open Science and FAIR science.

Usability Evaluation and Classification of mHealth Applications for Type 2 Diabetes Mellitus Using MARS and ID3 Algorithm.

The rapid growth of mHealth applications for Type 2 Diabetes Mellitus (T2DM) patients’ self-management has motivated the evaluation of these applications from both the usability and user point of view. The objective of this study was to identify mHealth applications that focus on T2DM from the Android store and rate them from the usability perspective using the MARS tool. Additionally, a classification of these mHealth applications was conducted using the ID3 algorithm to identify the most preferred application. The usability of the applications was assessed by two experts using MARS. A total of 11 mHealth applications were identified from the initial search, which fulfilled our inclusion criteria. The usability of the applications was rated using the MARS scale, from 1 (inadequate) to 5 (excellent). The Functionality (3.23) and Aesthetics (3.22) attributes had the highest score, whereas Information (3.1) had the lowest score. Among the 11 applications, “mySugr” had the highest average MARS score for both Application Quality (4.1/5) as well as Application Subjective Quality (4.5/5). Moreover, from the classification conducted using the ID3 algorithm, it was observed that 6 out of 11 mHealth applications were preferred for the self-management of T2DM.

What is a smart office environment? An exploratory study from a user perspective

PurposeThis paper aims to explore the meaning of smart office environments from a user perspective by investigating user preferences and expectations.Design/methodology/approachEleven semi-structured interviews with the users after moving into a smart office building of a Dutch Municipality and an observation as complementary data were conducted. The data were analysed based on the grounded theory and thematic analysis, combining a reflexive approach to the literature review.FindingsTwo main themes were revealed addressing user expectations and preferences for smart office environments: “enhanced interaction” with the social and physical office environment and “sense-making” of the smart concept (or smartness). Within these themes, basic and smart office aspects were identified and classified based on their association with smart office concepts or technology.Practical implicationsThe findings reveal the meaning of the smart office concepts from a user perspective by highlighting the importance of user experience on enhanced interaction and sense-making of the smart office concept, equipped with basic and smart aspects.Originality/valueTo the best of the authors’ knowledge, this study is the first to qualitatively examine drivers underlying the meaning of smart office concepts from a user point of view. Organisations, environmental psychologists, designers and managers can use the findings of this study to develop guidelines for a successful smart office design.

A Survey on Mobile App Development Approaches With the Industry Perspective

Mobile applications (i.e., mobile apps) are dynamic from the user point of view, it is complex in some situations, and it is being developed in competitive and strict time frames. Therefore, the developers are required to pay attention to choose an appropriate software development process to cater these needs. Over the last decade, agile approaches have become very popular for software development in general, but there has only been limited research performed in the applicability of agile methods in the area of mobile app development. In this paper, a detailed review on mobile app development approaches with their best practices is prepared to explore the suitability of agile approaches. We have also conducted an online survey to know the current mobile app development trends in industries. It is observed that the agile approaches are the most suited approaches for mobile app development due to its flexibility in making changes, scalability, usability, etc. This crucial survey contributes towards a better comprehension of development trends in mobile app development industries.

Use of MARC21 control field data in University Library OPACs in Karnataka: A study

This study discusses about importance of MARC21 control field and its effective implementation in university libraries OPACs in Karnataka. The catalogue records available through library web OPACs of universities under study formed the data source for this study. The university library web OPACs which we examined in this study have used Koha ILMS. One thousand and eighty-eight (1088) records were randomly selected from the nine university library web OPACs for the study. The study examined the proper implementation of 008 control field of MARC21, which is an important data element in information retrieval. The study found that average length of a cataloguing record was 1572.78 characters. The study as also revealed that libraries web OPACs under study have given scant attention for control fields, 001 and 003 were the two tag numbers that have been used extensively. Overall the university libraries have neglected control fields data element in their OPACs. This adversely affect the data retrieval from the user point of view. The study strongly recommend that libraries should fill up the data required for control fields while cataloguing their records.

Pembuatan Web Unit Produksi Coffee Santri di Aziz Paradise

Along with the development of technology, the need for information can trigger services that are easier, faster and more practical, especially in doing business. Entrepreneurs today are competing with each other to innovate, almost all businesses, both medium and small businesses use technology to increase promotion of places and products. To attract buyers, an attractive website appearance is needed so that it can increase the attractiveness of buyers. In this study, we propose an attractive website display design using the Laravel framework and with a drink menu recommendation feature based on certain diseases and based on mood with the KNN Algorithm with the prototype method. To ensure that the website can be accepted by users, a system assessment is carried out from a user point of view using User Acceptance Testing (UAT). It was found that the system received an "Agree" rating after the UAT average score, meaning that the web-based application of the Coffee Santri Production Unit in Aziz Paradise succeeded in meeting the system standards desired by the user.

BCI-based games and ADHD

Attention Deficit Hyperactivity Disorder (ADHD) is a neurological condition characterized by cognitive task difficulty, impulsivity, hyperactivity and loss of attention. It can persist into adulthood with negative academic and socio-professional outcomes. Neurofeedback treatments have been shown as effective for training the attention ability in children with ADHD. It has been found that interactive multi-player games are ideal from a therapeutic and long-term usage point of view due to their higher social motivation and cooperation among children with ADHD. In this study we conducted a semi-systematic review, with the goal of gathering findings from empirical and theoretical works in order to deepen our understanding about the use of Brain Computer Interface (BCI)-based for children and adults with ADHD, as a method to ameliorate the symptoms of their disorder.

Examining E-learning as an alternative solution to conventional learning during and post Covid-19 in Nigeria.

It is no longer news that the novel Corona Virus pandemic (COVID-19) is ravaging and still destroying the world, killing so many people and sending economies in different countries into recession. COVID-19 came as a thief in the night in the household of traditional schooling. Gradually, the face-to-face traditional way of teaching and learning was immediately put on hold and all parties running to their shelves for cover as measure to avert the spread of the dreaded virus. What came up as a viable alternative to face-to-face or conventional mode of teaching-learning in school and higher institution is E-learning. So many of these educational institutions had to resort to learning through some E-learning platforms which include ZOOM, YouTube, Google Meet, Google Classroom, Duo, Free Conference Call, etc. This established the fact that majority of the organizations have made an instant switch to online collaboration inclusive of schooling systems. This paper therefore sort to examine how Nigerian schools are reshaping the schooling/education system as to align with the alternative model of teaching-learning most essentially as E-learning rest on major pillars which are undoubtedly deficient in Nigeria and amongst Nigerians. There are challenges to overcome in achieving the e-learning phenomenon in Nigeria, many students without reliable internet access, power supply and technology struggle to participate in digital activities, which hinder online learning. The paper was approached in an E-learning subscriber or user point of view around FCT Abuja metropolis which includes teachers and learners (students/pupils). Questionnaires were distributed to the E-learning users and also the teachers of E-learning. Data were collected and analyzed using percentage method and Likert method to arrive at a conclusion and useful recommendations were made to enhance e-learning during and post COVID-19 in the various educational institutions in Nigeria.

``I don't care about cookies!" Platform Data Disclosure and Time-Inconsistent Users

Time-inconsistent internet users neglect future privacy costs and release too much data to be monetized by digital platforms. We study how regulations that require user consent for data processing affect platform profits, welfare and user surplus, depending on business models and the degree of time inconsistency. Consent mechanisms increase user surplus or welfare only if their design facilitates consent refusal. If platforms can make it difficult to opt out, it may be better for society as a whole if the former choose the disclosure level, even though it tends to be excessive from a user point of view. Voluntary caps on usage, as recently adopted by some platforms, can raise profits by making some users consent to more disclosure.