iOS Mobile Platforms Research Articles

User Interface Design for the Orca Music Player Mobile Application

The rapid development in the field of information technology has resulted in a significant change in the way music is listened to. The current digital generation prefers to listen to music online through their digital devices. Thus, designing User Interface and User Experience on Mobile Music Player Applications using the User Centered Design method which consists of Plan the human centered process, Specify the context of use, Specify user and organizational requirements, and Produce design Solution. The target audience for this design is productive age children 15-35 years old with product limitations that only reach the prototype stage and feature services that are still lacking. The platform used is the android and ios mobile platform and UI design by making Wireframe of the application design.

A GCC Artificial Food Additives Management based Mobile Application Development

Artificial food additives pose significant health risks to Gulf Cooperation Council (GCC) citizens despite regional authorities' extensive medical, legislative, and technological efforts. Literature highlights the detrimental impacts of these additives, including malnutrition, digestive disorders, respiratory problems, skin issues, hives, nausea, diarrhea, shortness of breath, allergic reactions, high blood pressure, and tumors. The research project at hand aims at becoming the first official and comprehensive mobile application of its own in the GCC region that manages the calculation and demonstration of an up-to-date health and legal knowledge base of the impacts of artificial additives, enhances the awareness, automatically recognizes the artificial additives, and provides alternative solutions, for both android and IOS mobile platforms. This research project introduces "Weqaya," a pioneering mobile application designed to manage, educate, and raise awareness about the effects of artificial additives. Weqaya provides real-time health and legal information, identifies additives, and suggests alternative solutions for Android and iOS platforms. The project employs an Agile-based SDLC model to explore, develop, and evaluate the food additive phenomena in Weqaya. The application's usability evaluation scores a promising 95.21%, indicating its potential utility for GCC health ministries, dietitians, academics, researchers, and food producers in enhancing knowledge and promoting non-artificial food options.

(117) Interrater Agreement and Feasibility of Three-Dimensional Photography for Curvature Assessment in Peyronie's Disease

Abstract Introduction Curvature assessment is an iterative aspect of the evaluation of Peyronie’s Disease (PD); its accuracy is subject to patient erection quality and clinician technique. Prior studies have shown promising results when using 3D modeling software in curvature assessment, yet none have applied the technology to human subjects with complex PD in an authentic clinical scenario. Objective To evaluate the feasibility of using 3D modeling to assess penile deformity in PD patients. Methods MirrorMe3D is a HIPPA-compliant iOS mobile and web-based platform designed for 3D anatomical modeling. 2 trained urology fellows (coders 1 and 2) were trained to create models using the app by acquiring ≥ 12 images of the target obtained in a multiplanar, 360-degree fashion. Participants verbally consented to deidentified penile photography during their clinic visit for penile curvature assessment with Doppler ultrasound (CADUS). Photographs were obtained prior to performing DUS with the patient in the supine position and using a commercially available clip-on ring light and custom 3D-printed holder device placed over the penis base for stabilization. 3D models were generated upon completion of the visit and screened for quality. Curvature assessment on the 3D images included curvature direction, location, degrees, and other defects identified via visual inspection of the digital model. Results 7 unique, quality 3D images were generated using 15-20 photos per participant (Figure 1). The time required to obtain images was 1-2 minutes. Once the 3D image was developed, the curvature assessment took about 5 minutes. Quantitative results are summarized in Table 1. We observed a high rate of agreement in terms of primary direction of curvature and an acceptable variance rate when evaluating degrees of curvature within a margin of 10°; of note, coders were in agreement with each other to within a 10° margin 100% of the time (7/7 patients). We also observed a high agreement rate when evaluating the presence of absence of tapering but low agreement when assessing for the presence of indentation and hourglass deformity. Regarding the penis stabilizer, our experience suggests that it may alter the base of the penis anatomy, but it improves capture of the organ with diminished interference from surrounding anatomy (scrotum, abdomen). Factors influencing the quality of the image were exam room set-up, patient anxiety about losing an erection, lighting, and body hair. Conclusions 3D image-based PD assessment can be implemented with minimal impact to visit efficiency. The 3D technique does not appear to reproduce complex PD measurements obtained by CADUS; however, future studies will evaluate the utility of employing this technology to a larger cohort and also to monitor treatment effect in complex PD patients. Disclosure No.

Методи та засоби Покращення точності розпізнавання об’єктів на мобільній платформі ios в реальному часі

As a result of the analytical review, it was established that the family of Yolo models is a promising area of search and recognition of objects. However, existing implementations do not support the ability to run the model on the iOS platform. To achieve these goals, a comprehensive scalable conversion system has been developed to improve the recognition accuracy of arbitrary models based on the Docker system. The method of improvement is to add a layer with the Mish activation function to the original model. The method of conversion is to quickly convert any Yolo model to CoreML format. As part of the study of these techniques, a model of the neural network Yolov4_TCAR was created. Additionally, a method of accelerating the load on the CPU using an additional layer of neural network with the function of activating Mish in Swift for the iOS mobile platform was added. As a result, the effectiveness of the Mish activation function, the CPU load of the mobile device, the amount of RAM used, and the frame rate when using the improved original Yolov4-TCAR model were studied. The results of the research confirmed the functioning of the algorithm for conversion and accuracy increase of the neural network model in real-time.

Research and Development of Smart Home Security System Based on Wechat Control

With the improvement of living standards, people’s requirements for safety and comfort gradually improve, which requires us to constantly improve home security. With the rapid development of the Internet of things (hereinafter referred to as IOT), we have set up a smart home security system (hereinafter referred to as SHSS), which can be controlled by wechat. Through the IOT technology, the SHSS can contact various subsystems according to the needs of users, including lighting control, security protection, fire prevention and anti-theft, which will bring more humanized operation experience. Through wireless communication technology, we can monitor all kinds of indoor environment in real time, which will prevent illegal intrusion and other behaviors. At the same time, with the popularity of Android, IOS and other mobile platforms, SHSS has been developed into a variety of applications, such as wechat, which can realize remote control of indoor devices. Firstly, this paper analyzes the overall architecture and control module of SHSS. Then, this paper analyzes various subsystems, which can complete the system development in more detail.

Effect of Release Timing of App Innovations based on Mobile Platform Innovations

ABSTRACT This study focuses on app innovations based on mobile platform innovations (MPIs), examining how app developers can time the app innovations release to best leverage MPIs and increase app financial performance. We suggest that the performance is contingent on the adoption curve of mobile platform generations and the level of backward compatibility of the MPIs. We find support for our hypotheses after analyzing 1,213 MPI-based app innovations on the iOS mobile platform ecosystem. The main theoretical contribution of this study, supported empirically, is to better understand the role of the platform generation adoption curve and MPIs’ level of backward compatibility in the assessment of the effect of MPI-based app innovation release timing on complementor’s performance. We encourage third-party developers to create MPI-based app innovations more prominently and release them early during the growth stage of the adoption curve while prioritizing MPIs with no backward compatibility.

Методи пошуку та розпізнавання об'єктів у відеозображеннях на мобільній платформі IOS в реальному часі

Методи пошуку та розпізнавання об'єктів у відеозображеннях на мобільній платформі IOS в реальному часі

Development of Augmented Reality Application for Interactive Smart Materials

The paper presents research related to thermochromic inks printed on textile materials. These types of materials are smart materials, they act as packaging indicators, and we use them to develop a software application on mobile devices. That application identifies the most significant changes in parameters of the goods contained in the packaging, such as temperature changes during the storage and transport (goods packaged in packaging that is sensitive to heat), or such as pharmaceuticals and frozen food, etc. This paper aims to demonstrate the possibility of connecting thermochromic materials and Augmented Reality technology through the development of an application for identifying thermochromic materials changes. The tested samples were printed on the textile with a screen printing technique with conventional and thermochromic leuco inks on various textile materials. The Augmented Reality platform Vuforia was used for developing a software application for mobile devices. The application was developed for the iOS mobile platform. The result of the research is the functional application that actively monitors and displays changes in thermochromic materials due to temperature changes, which identifies the effect of heat on the goods in textile packaging.

Augmented reality virtual glasses try-on technology based on iOS platform

With the development of e-commerce, network virtual try-on, as a new online shopping mode, fills the gap that the goods cannot be tried on in traditional online shopping. In the work, we discussed augmented reality virtual glasses try-on technology on iOS platform to achieve optimal purchase of online glasses, improving try-on speed of virtual glasses, user senses of reality, and immersion. Face information was collected by the input device-monocular camera. After face detection by SVM classifier, the local face features were extracted by robust SIFT. Combined with SDM, the feature points were iteratively solved to obtain more accurate feature point alignment model. Through the head pose estimation, the virtual model was accurately superimposed on the human face, thus realizing the try-on of virtual glasses. The above research was applied in iOS glasses try-on APP system to design the try-on system of augmented reality virtual glasses on iOS mobile platform. It is proved that the method can achieve accurate identification of face features and quick try-on of virtual glasses.

A Systematic Evaluation of Mobile Applications for Instant Messaging on iOS Devices

Nowadays, instant messaging applications (apps) are one of the most popular applications for mobile devices with millions of active users. However, mobile devices present hardware and software characteristics and limitations compared with personal computers. Hence, to address the usability issues of mobile apps, a specific methodology must be conducted. This paper shows the findings from a systematic analysis of these applications on iOS mobile platform that was conducted to identify some usability issues in mobile applications for instant messaging. The overall process includes a Keystroke-Level Modeling and a Mobile Heuristic Evaluation. In the same trend, we propose a set of guidelines for improving the usability of these apps. Based on our findings, this analysis will help in the future to create more effective mobile applications for instant messaging.

The use of a smartphone application for fast lung cancer risk assessment†.

The overall prognosis of lung cancer is poor: Only every 8 patient survives 5 years after diagnosis. This outcome is partly attributable to late diagnosis. To implement a screening program for early diagnosis, selection of high-risk individuals is essential. Our aim was to construct a personalized lung cancer risk assessment tool using geographic localization to lead the high-risk individuals to the local health care provider. A smartphone application was created for Android and iOS mobile platforms using a risk assessment questionnaire. The software provides immediate classification into low, moderate and high-risk groups. The high-risk group is directed to the nearest screening centre based on GPS location. The complete test data set is recorded on a collection server database for further analysis. The application was downloaded 13 890 times and completed by 89 500 persons over a period of 20 months. The mean age of the tested users was 36.91 years (9-93 years); the majority were men living in an urban area (62.3%). The test was completed by 38 850 active smokers and 26 710 persons who reported having already quit smoking, resulting in 30 072 moderate and 10 740 high-risk users. This free application is an active communication tool for most smartphone owners. It helps those who might need further medical attention. The affected users can be easily connected and localized via the smartphone, which helps recruit individuals into screening programs.

P1.03-034 Implementing Smartphone Application in Early Lung Cancer Detection and Screening

The early detection of NSCLC cases is still the key point of the surgical treatment of lung cancer. Finding the symptomless patients require the system of risk assessment, risk group selection and a controlled screening. The modern communication path of the mobile devices are enabling us a complete new communication and selection method wich can effectively simplify the risk group identification and the suggestion of screening by the Screening Centers. The aim of our study was to determine the effectivity of a lung cancer risk assessment mobile application (LungScreen) in a localised setting. A freely downloadable lung cancer risk assessment application (LungScreen) were created for Android and iOS mobile platforms. The application calculates and shows individual NSCLC risk based on Bach's protocol after collecting demographic data, smoking status, and possible environmental harms of the participant. Based on GPS coordinates the high risk participant is navigated to the nearest Screening Center for further investigation. We analyzed the records of the application in a test period of one year aided by an informative campaign in Hungary. In one year test period more than 70000 participants downloaded and completed the risk assessment test (Male/Female 58%/42%, Age range 9-92 years, mean age 38,2 year). 14238 participants were active smokers, high risk criteria was calculated in 1831 cases, in which further screening investigation were suggested. In our region (Baranya County) 158 LDCT screening were performed, with 32 positive findings which required further investigations. In 9 cases Tumor Board decided to indicate surgery (7 cases NSCLC, 2 cases benign lesion). All the procedures were performed with VATS. 8028 tests from 28 other countries (e.g. Germany, France, UK, USA, Japan etc). Lung cancer risk assessment via mobile devices allows free, fast and efficient way to select, manage and localize high risk population for NSCLC. By omitting the complex recruitment process it can effectively fasten the screening trials and subsequently lower the financial needs. Giving immediate personalized feedback and individual direction to diagnostic centers can facilitate early diagnosis of operable NSCLC cases.

Contraception and Family Planning

INTRODUCTION: Ninety percent of American adults have cell phones and half of them download applications (apps). We conducted a review of mobile health apps related to contraception and family planning. The primary objective of our study was to identify the number and type of contraception-related mobile apps and to perform review of content of those apps. METHODS: We searched the iOS mobile platform for the key words related to contraception and family planning between June and July 2014. A total of 289 apps were identified of which 129 were excluded as a result of a lack of contraception related information. We performed review of the remaining apps to identify themes and categories. RESULTS: Of 160 apps with contraception-related content 16 (10%) were primarily targeted toward health care providers. These included journals textbooks and reference guides. A total of 144 (90%) apps targeted toward patients were menstrual cycle trackers (40) birth control reminders (26) games (16) sexual health information apps (40) and apps to locate family planning centers (22). Only 20 patient apps had comprehensive information about multiple birth control methods. CONCLUSION: Mobile apps are an increasingly used means of accessing medical information. Accurate and comprehensive information about contraception is available in few apps. IMPLICATIONS: We are planning to perform clinical studies to identify the usefulness of such apps in clinical care. These studies may help us to understand the role of mobile health apps as a supplement to clinical care.