prototype development
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10.2196/32458 ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. e32458
Author(s):  
Jennifer Huberty ◽  
Nishat Bhuiyan ◽  
Taylor Neher ◽  
Lynda Joeman ◽  
Ruben Mesa ◽  
...  

Background Mobile meditation apps may offer a long-term, accessible, and effective solution for ongoing symptom management in cancer patients/survivors. However, there are currently no commercial cancer-specific meditation apps that reflect cancer specialist expertise, input from cancer patients/survivors, and features and content specific to cancer patients’/survivors’ needs. Objective The aim of this study was to gain insight (via surveys, daily journals, and focus groups) from cancer patients/survivors, health care providers, and current subscribers of Calm (a consumer-based mobile meditation app) who were patients/survivors to develop a prototype of a mobile meditation app specifically designed for cancer patients/survivors. Methods Participants were recruited via prior partnerships, word-of-mouth referrals, and recruitment posts on Facebook and Instagram. Cancer patients/survivors and health care providers were instructed to download and use the Calm app for at least 10 minutes a day for 7 days, complete an online daily journal for 7 days, and participate in a virtual focus group (one for cancer patients/survivors and one for providers). Current Calm subscribers who were cancer patients/survivors completed an online survey about different aspects of the Calm app and participated in a third virtual focus group. Data were qualitatively analyzed using a combination of deductive and inductive coding. Results A total of 27 participants (11 cancer patients/survivors, 10 health care providers, 6 current Calm subscribers) completed the study. Similar themes and subthemes were found across surveys, daily journals, and focus groups, and fell into two major categories, content and functionality, with cancer-specific and noncancer-specific themes identified within each category. The majority of content preferences and suggestions that arose were cancer-specific, such as content related to negative emotions or feelings (eg, anxiety, grief, trauma/posttraumatic stress disorder, fear of recurrence, isolation), positive feelings and finding meaning (eg, gratitude, storytelling, acceptance), scenarios and experiences (eg, waiting, treatment-specific mediations), type and stage of cancer journey, and movement modifications. Some of the noncancer-specific themes under app content included sleep, music, and visualizations. In terms of app functionality, the majority of participants expressed interest in having a section/tab/area of the app that was specifically geared toward cancer patients/survivors. Preferences and suggestions for cancer-specific functionality features included options based on symptoms or journey, being able to communicate with other patients or survivors to share suggestions for specific meditations, and having an emergency toolkit for patients/survivors. Conclusions Findings from cancer patients/survivors, health care providers, and current Calm subscribers who were patients/survivors to be incorporated into the development of the prototype fell into two major categories: (1) content of the app and (2) functionality of the app. The prototype’s form and function will be pilot-tested among 30 cancer patients/survivors in a 4-week study, and the resulting feasibility data will be used to inform the final app design and an efficacy study.


2022 ◽  
Vol 2022 ◽  
pp. 1-18
Author(s):  
Dereje Tekilu Aseffa ◽  
Harish Kalla ◽  
Satyasis Mishra

Money transactions can be performed by automated self-service machines like ATMs for money deposits and withdrawals, banknote counters and coin counters, automatic vending machines, and automatic smart card charging machines. There are four important functions such as banknote recognition, counterfeit banknote detection, serial number recognition, and fitness classification which are furnished with these devices. Therefore, we need a robust system that can recognize banknotes and classify them into denominations that can be used in these automated machines. However, the most widely available banknote detectors are hardware systems that use optical and magnetic sensors to detect and validate banknotes. These banknote detectors are usually designed for specific country banknotes. Reprogramming such a system to detect banknotes is very difficult. In addition, researchers have developed banknote recognition systems using deep learning artificial intelligence technology like CNN and R-CNN. However, in these systems, dataset used for training is relatively small, and the accuracy of banknote recognition is found smaller. The existing systems also do not include implementation and its development using embedded systems. In this research work, we collected various Ethiopian currencies with different ages and conditions and applied various optimization techniques for CNN architects to identify the fake notes. Experimental analysis has been demonstrated with different models of CNN such as InceptionV3, MobileNetV2, XceptionNet, and ResNet50. MobileNetV2 with RMSProp optimization technique with batch size 32 is found to be a robust and reliable Ethiopian banknote detector and achieved superior accuracy of 96.4% in comparison to other CNN models. Selected model MobileNetV2 with RMSProp optimization has been implemented through an embedded platform by utilizing Raspberry Pi 3 B+ and other peripherals. Further, real-time identification of fake notes in a Web-based user interface (UI) has also been proposed in the research.


2022 ◽  
Author(s):  
Elissa Florentina ◽  
Stacia Andani Fortunata ◽  
Nila K. Hidayat ◽  
Maria D.P.T. Gunawan-Puteri

2022 ◽  
Vol 28 (1) ◽  
pp. 146045822110695
Author(s):  
Jade Yi Ming Ng ◽  
Tong Wah Lim ◽  
Natasya Tarib ◽  
Ting Khee Ho

Effective delivery of post-insertion instructions is essential for denture care and oral health. This study aimed to develop a progressive web application (PWA) to educate patients’ chairside and serve as a reference material. A need analysis was conducted before prototype development. Subsequently, the prototype was subjected to content verification, design appraisal and usability testing. The results of usability testing revealed a user task success rate of 94.4%, with an adjusted Wald 95% confidence interval of 83–100%. User satisfaction assessed using the Single Ease Questionnaire and System Usability Score reported a mean score of 6.13 (95% CI: 5.69–6.55) and 85.9 (95% CI: 82.2–89.6), respectively, indicating good usability. This study highlights the systematic approach of developing an evidence-based educational PWA to meet the usability standards for mobile applications. This PWA is useful in clinical studies to explore mobile technologies’ potential in educating denture wearers, especially in the older population.


ACTA IMEKO ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 73
Author(s):  
Rosario Morello ◽  
Laura Fabbiano ◽  
Paolo Oresta ◽  
Claudio De Capua

Gastric disorders are widely spread among the population of any age. At the moment, the diagnosis is made by using invasive systems that cause several side effects. The present manuscript proposes an innovative non-invasive sensing system for diagnosing gastric dysfunctions. The Electro-GastroGraphy (EGG) technique is used to record myoelectrical signals of stomach activities. Although EGG technique is well known for a long time, several issues concerning the signal processing and the definition of suitable diagnostic criteria are still unresolved. So, EGG is to this day a trial practice. The authors want to overcome the current limitations of the technique and improve its relevance. To this purpose, a smart EGG sensing system has been designed to non-invasively diagnose gastric disorders. In detail, the system records the gastric slow waves by means of skin surface electrodes placed in the epigastric area. Cutaneous myoelectrical signals are so acquired from the body surface in proximity of stomach. Electro-gastrographic record is then processed. According to the diagnostic model designed from the authors, the system estimates specific diagnostic parameters in time and frequency domains. It uses Discrete Wavelet Transform to obtain power spectral density diagrams. The frequency and power of the EGG waveform and the dominant frequency components are so analyzed. The defined diagnostic parameters are put in comparison with the reference values of a normal EGG in order to estimate the presence of gastric pathologies by the analysis of arrhythmias (<em>tachygastria</em>, <em>bradygastria</em> and irregular rhythm). The paper aims to describe the design of the system and of the arrhythmias detection algorithm. Prototype development and experimental data will be presented in future works. Preliminary results show an interesting relevance of the suggested technique so that it can be considered as a promising non-invasive tool for diagnosing gastrointestinal motility disorders.


Electricity ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 1-15
Author(s):  
Simon Thomy ◽  
Xavier Margueron ◽  
Jean-Sylvio Ngoua Teu Magambo ◽  
Reda Bakri ◽  
Philippe Le Moigne

Conceiving planar magnetic components for power electronic converters is very constraining, especially in the case of prototype development. Indeed, such making requires skills, specific appliances as well as human time for setting up the machine tools and the fabrication process. With the emergence of Fabrication Laboratory (FabLab), conceiving of planar copper foil prototypes becomes more feasible in a shortened time process for engineers and researchers. This paper presents a methodology and process for conceiving power planar transformers with the help of machines and tools that can be found in the usual FabLab.


2021 ◽  
Vol 8 (3) ◽  
Author(s):  
Syed Hasan Mehdi Mehdi ◽  
Rajanikant Arya

Electricity is the fundamental need of human society. Any nation's growth depends on energy. The worldwide electricity consumption increases and conventional electricity sources are causing pollution. Therefore, some non-conventional energy recourses are mandatory to be designed and developed for electricity generation, and they are useful and environment-friendly. In this study, a renewable, non-conventional energy source prototype has been developed, based on the mechanism of power generation from speed breaker with ratchet and pawl mechanism. This study aims to convert the kinetic energy of vehicles into electrical energy which can be used for street and highway lighting and conservation of electrical energy.


2021 ◽  
Author(s):  
◽  
Richard Dodds

<p>Video games are increasingly seen as a meaningful form of art and storytelling. A common critique of video games is that the player’s in-game actions can easily become disconnected from their character and the storyline, referred to as Ludo-narrative dissonance. To date, no published academic research has been carried out on how to avoid Ludo-narrative dissonance from a game systems level. Yet, the development of Ludo-narrative consistent game systems have the potential to enhance gameplay and player satisfaction. The aim of this research was to develop a prototype ludo-narrative consistent game system, and to explore the design requirements, strengths and challenges of this prototype system. This was achieved through the development of a prototype video game. The prototype incorporated a trait system that assigned personality traits to the player character based on their style of gameplay, consequently altering the storyline in a way that was aligned with the player’s actions. This prototype was user tested by twenty-one participants, who were recruited via convenience sampling. The participants played the prototype three times, then completed an anonymous survey on their experience of playing the game. I observed their play remotely via Zoom and was available to them for answering questions. The prototype was updated based on my observations and user testing survey responses. The prototype development process, my observations of user testers, and the survey results, provided unique insights into the design requirements, strengths and weaknesses of the prototype trait system. My research illustrates that narrative systems and game mechanics are closely interconnected in the development of a trait system. Furthermore, my research shows that when implementing a trait-based system it is important to consider the following design requirements, including; trait interaction, action weighting, mechanical cohesion and consideration of player intentions. User testing observations and survey results highlighted some design challenges that provided insights for the improvement of the prototype. One insight was how the mechanical difficulty of the game affected the assignment of traits, making some personality traits easier to achieve than their counterparts. This was addressed by increasing the difficulty and adjusting the action weighting of opposing traits. Another insight was from situations when participants falsely attributed certain play behaviours to the traits they were assigned. These false attributions provided additional ideas for the updated prototype. In conclusion, this research contributes to the overall body of knowledge in game design, by illustrating the design requirements, challenges and strengths of a prototype Ludo-narrative consistent game system.</p>


2021 ◽  
Author(s):  
◽  
Richard Dodds

<p>Video games are increasingly seen as a meaningful form of art and storytelling. A common critique of video games is that the player’s in-game actions can easily become disconnected from their character and the storyline, referred to as Ludo-narrative dissonance. To date, no published academic research has been carried out on how to avoid Ludo-narrative dissonance from a game systems level. Yet, the development of Ludo-narrative consistent game systems have the potential to enhance gameplay and player satisfaction. The aim of this research was to develop a prototype ludo-narrative consistent game system, and to explore the design requirements, strengths and challenges of this prototype system. This was achieved through the development of a prototype video game. The prototype incorporated a trait system that assigned personality traits to the player character based on their style of gameplay, consequently altering the storyline in a way that was aligned with the player’s actions. This prototype was user tested by twenty-one participants, who were recruited via convenience sampling. The participants played the prototype three times, then completed an anonymous survey on their experience of playing the game. I observed their play remotely via Zoom and was available to them for answering questions. The prototype was updated based on my observations and user testing survey responses. The prototype development process, my observations of user testers, and the survey results, provided unique insights into the design requirements, strengths and weaknesses of the prototype trait system. My research illustrates that narrative systems and game mechanics are closely interconnected in the development of a trait system. Furthermore, my research shows that when implementing a trait-based system it is important to consider the following design requirements, including; trait interaction, action weighting, mechanical cohesion and consideration of player intentions. User testing observations and survey results highlighted some design challenges that provided insights for the improvement of the prototype. One insight was how the mechanical difficulty of the game affected the assignment of traits, making some personality traits easier to achieve than their counterparts. This was addressed by increasing the difficulty and adjusting the action weighting of opposing traits. Another insight was from situations when participants falsely attributed certain play behaviours to the traits they were assigned. These false attributions provided additional ideas for the updated prototype. In conclusion, this research contributes to the overall body of knowledge in game design, by illustrating the design requirements, challenges and strengths of a prototype Ludo-narrative consistent game system.</p>


2021 ◽  
Vol 2135 (1) ◽  
pp. 012001
Author(s):  
Angie Alonso ◽  
Andres Peña ◽  
Fredy Martínez

Abstract The rapid spread of the SARS-CoV-2 virus has highlighted many social interaction problems that favor the spread of disease, particularly airborne spread, which can be addressed by adjusting existing systems. Of particular interest are places where large numbers of people interact, as they become a focus for the spread of these diseases. This paper proposes and evaluates an autonomous identification scheme for certain surfaces considered high risk due to their continuous handling. These high-contact surfaces can be identified by an autonomous system to apply specific cleaning tasks to them. We evaluate three convolutional models from a proprietary dataset with a total of 2000 images ranging from wall switches to water dispensers. The objective is to identify the ideal architecture for the system. The ResNet (Residual Neural Network), DenseNet (Dense Convolutional Network), and NASNet (Neural Architecture Search Network) models were selected due to their high performance reported in the literature. The models are evaluated with specialized metrics in non-binary classification problems, and the best scheme is selected for prototype development.


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