Smartphone Platform Research Articles

Impact of the Mobile App "Cognogene" on University Students' Communication Skills

Introduction: The notion of electronic mental health care is suggested in today's world. With the aid of this care, people's talents are no longer limited by time or location, and those in need of mental health care can get these services by downloading and installing software on their mobile devices. The Cognogene application software has been created to provide electronic mental health services on the smartphone platform. This study aimed to measure the impact of the mobile app "Cognogene" on university students' communication skills. Method : The statistical population of this study included 104 students studying at Tehran University in the winter semester (2021 -2022). They were randomly divided into two 54 -member groups (experimental and control). The experimental group received electronic psychological education (consisting of short video clips, daily homework, motivational letters, etc.) in 21 sessions, while the control group did not. To collect data, Queen Dom's communication skills questionnaire was used in two stages: pre -test and post -test. The data were analyzed using the one -way analysis of variance. Results: Results showed that the intervention made a significant difference in the mean score of all components of the study of communication skills except the components of "receiving and sending messages" and "emotional control". Conclusion : This finding suggests that training through the Cognogene application can be used as a complement to other training methods to improve communication skills.

Hollow NiCo@C Nanozyme-Embedded Paper-Based Colorimetric Aptasensor for Highly Sensitive Antibiotic Detection on a Smartphone Platform.

Antibiotic residues in the environment and in foods pose a serious threat to ecosystems and human health. Developing sensitive and on-site detection methods is therefore in high demand. In this work, a portable paper-based colorimetric sensor with a smartphone platform with an ultrahigh sensitivity has been designed for on-site and quantitative analysis of antibiotic residues based on aptamer-regulated nanozyme activity. The developed excellent peroxidase-like nanozymes, carbon-protected NiCo bimetal oxides with a unique hollow nanocage structure (NiCo@C HCs), could effectively catalyze the oxidation of chromogenic substrates by H2O2. Once bound to a specific aptamer, the enzyme-mimicking activity of NiCo@C HCs is obviously inhibited as a result of the masking of active sites but could be restored via the target-aptamer recognition. Herein, the aptamer-modified NiCo@C HCs are embedded on paper pieces to construct paper-based biochips for visual detection. Meanwhile, a smartphone platform is integrated for the signal readout. Using enrofloxacin (ENR) as an analyte model, the proposed paper-based analysis platform shows a reliable and sensitive detection of ENR with an ultralow detection limit of 0.029 ng/mL. The platform also works well in various real samples. This analysis method is facile in design, showing a great application potential for on-site and mass screening of antibiotic residues in the environment and in foods.

Facile Synthesis of Fe-Doped Hydroxyapatite Nanoparticles from Waste Coal Ash: Fabrication of a Portable Sensor for the Sensitive and Selective Colorimetric Detection of Hydrogen Sulfide.

In this work, a new strategy has been reported for the portable detection of H2S based on Fe-doped hydroxyapatite nanoparticles (Fe-HA) using a colorimetric paper test strip integrated with a smartphone platform. Fe-HA NPs were fabricated successfully via recycling waste coal ash. The obtained probe response toward H2S was through a distinct visual color change. The sensing mechanism is based on the displacement reaction, in which PO4 3- is replaced by S2-. The prepared test strip shows high selectivity, and the other compounds containing thiol and sulfur anion have a negligible effect on the detection of H2S. The designed scheme is applied for H2S detection in the concentration range of 0.5-130 ppm with a limit of detection of 70 ppb. Furthermore, such a disposable sensor was used as a practical system for monitoring H2S in actual water samples, suggesting the promising potential of this platform for suitable analysis of H2S in an aqueous environment.

Design of Mobile 3D Augmented Reality on Marker Visual Inspection Mask

Augmented reality is a ground-breaking technology that allows users to communicate with an enticing real-world experience to receive messages or knowledge. Today, mask inspection is essential to relay information to society through an augmented reality where extensive information about masks is required and identifying them is challenging. Furthermore, with augmented reality, society may have access to the fascinating way of getting information on the masks, assisting in spreading knowledge, particularly during this pandemic. The augmented reality on a visual inspection mask (ARVIM) was created utilizing 3D images on an Android smartphone platform. The models were created using Blender Animation and Unity 3D software. Vuforia Engine and Android Studio applications were used to build a personalized mobile Augmented Reality application. Google Cloud was used to store data that are accessible to users. ARVIM has facilitated teaching and interaction with 3D AR effects enjoyable for users. The analysis results on the use of ARVIM revealed that ARVIM obtained a high easiness rating of 80%. While 83% of respondents say ARVIM can help distinguish between different types of masks, 88% of respondents agreed that ARVIM's design is acceptable and approachable. This initiative enhances society's education in interactive and mixed-reality innovation settings through a long-distance and innovative teaching method that gives a comprehensive Google Platform experience.

Smartphone platform based on gelatin methacryloyl(GelMA)combined with deep learning models for real-time monitoring of food freshness

Real-time monitoring of food freshness remains a challenge both for food industry and consumers since no detection devices with portability, affordability and efficiency has been commercialized to date. Here, we developed a facile sensing platform based on a smartphone application (APP) with incorporation of a deep-learning model for the real-time monitoring the food freshness. The colorimetric indicator bars on a cellulose paper were firstly constructed through the gelatinization of synthesized gelatin methacryloyl (GleMA) via UV-induced crosslinking with encapsulation of bromocresol green (BCG). After taking photos, the deep-learning model with convolutional neural network (CNN) was trained using 1735 images of labeled bars and then well predicts the meat freshness with an overall accuracy of 96.2%. Meanwhile, integrating VGG 16 architecture for the CNN and marked-based watershed algorithm into a smartphone APP could make consumers recognize the meat freshness within 30 s by simply scanning the packaging. Our sensing platform was verified as sensitive, automatic and non-destructive, which has a potential application both for food industry and consumers to real-time monitor the food freshness.

Rare-earth ions coordination enhanced ratiometric fluorescent sensing platform for quantitative visual analysis of antibiotic residues in real samples

Levofloxacin (LVFX) as a representative drug of quinolone antibiotics is widely used in clinical, and its residues enriched in water bodies and sideline products seriously damage human health. It is imperative to develop a real-time/on-site sensing method for monitoring residual antibiotics. Here, we report a portable sensing platform by utilizing a composite fluorescent nanoprobe constructed by the cerium ions (Ce3+) coordination functionalized CdTe quantum dots (QDs) for the visual and quantitative detection of LVFX residues. This fluorescent probe provides a distinct color variation from red to green, which shows a good linear relationship to LVFX residues concentrations in the range of 0-6.0 µmol/L with a sensitive limit of detection (LOD) of 16.3 nmol/L. The smartphone platform with Color Analyzer App installed, which could accomplish quantified detection of LVFX in water, milk, and raw pork with a LOD of 27.9 nmol/L. The facile sensing method we proposed realizes rapid visualization of antibiotics residual in the environment and provides a practical application pathway in food safety and human health.

App store governance: Implications, limitations, and regulatory responses

Events such as the riot at the United States Capitol and tightening constraints on the Russian public sphere have highlighted the socio-political significance of app store governance. This is dominated by Apple and Google as operators of the two largest smartphone platforms. In this article, we analyse two case studies: the removals from app stores in 2021 of the fringe American social media app Parler and of the Russian opposition app Smart Voting. On the basis of this analysis, we identify three critical limitations for app store governance at present: Apple's and Google's dominance, the substantive opacity of their respective app store guidelines, and the arbitrariness with which these guidelines are applied to specific cases. We then assess the potential efficacy of legislative proposals in the EU and US to intervene in this domain and conclude by offering some recommendations supporting more efficacious and socially responsible app store governance.

Picture superiority effect in authentication systems for the blind and visually impaired on a smartphone platform

Picture superiority effect in authentication systems for the blind and visually impaired on a smartphone platform

OneBusAway Multi-Region – Rapidly Expanding Mobile Transit Apps to New Cities

Real-time transit information offers many benefits to transit riders, including reduced wait times and increased customer satisfaction. However, offering real-time transit services has been challenging for many transit agencies. While mobile applications (apps) have emerged as a preferred dissemination method for real-time information, it is typically cost-prohibitive for transit agencies to fund custom development of native mobile apps for all popular smartphone platforms. Third-party developers can offer services if an agency openly shares real-time data, but these individuals are volunteers whose priorities and deadlines may not be the same as the agency’s. As a result, few cities have full app portfolios that cover all smartphone platforms. This paper presents the OneBusAway multi-region project, a collaborative effort that is enabling the rapid expansion of native mobile transit apps to new cities. OneBusAway is an open-source transit information system that has provided real-time transit services to the Puget Sound (Washington) area since 2008. The new OneBusAway multi-region feature expands the coverage of the existing Android, iPhone, Windows Phone, and Windows 8 apps for OneBusAway to new cities, including Tampa and Atlanta. The multi-region system architecture, collaborative design and development process, and lessons learned from this ground-breaking project are discussed. The fundamental shift from proprietary to open-source software in the transit industry that has made this type of project possible also is examined.

Analyzing field audio of parent-child book reading activities across various audio capture devices

Language ENvironment Analysis (LENA) is a light weight audio capture device commonly used to monitor language including frequency of parent-child interactions for research purposes. However, various factors including price and technical limitations often limit the use of LENA for low-income families. Using a smartphone can be a feasible alternative when LENA is not available to practitioners/families. Over the past three decades, significant advancements have resulted in smartphone platforms/microphones/technology, allowing for high quality recorded audio which are available in most households. In this study we compare audio quality and measure performance of several Automatic Speech recognition (ASR) engines on audio captured from iPhone and Android relative to LENA devices. Families who consented in this study recorded reading activities with their children at home using both personal smartphones and LENA. Some challenges we found include recording synchronization, unnecessary background noises, and uneven room acoustics. Audio quality comparison is measured using Speech-Signal-to-noise ratio (SSNR) metric. Both open-source and fine-tuned ASR models are explored, with results reported using overall Word Error Rate (WER), as well as separated by speaker–Child versus Adult. Results show that smartphone platforms can be used versus LENA for child-adult language assessment. [Work sponsored by NSF through Grant Nos. 1918032 and 1918012.]

Portable smartphone platform integrated with paper strip-assisted fluorescence sensor for ultrasensitive and visual quantitation of ascorbic acid

It is significant to develop low-cost, sensitive, and portable sensing platform for point-of-care testing of ascorbic acid (AA) in food quality evaluation. Herein, a smart point-of-care (SPOC) sensor, consisting of fluorescent paper chip, 3D printed-accessories and smartphone, was developed for ultrasensitive and visual quantitative detection of AA. Fluorescent paper chip was made through printing silicon doped carbon dots (SiCDs)-Fe3+ as “ink” onto filter paper, in which SiCDs emitting strong fluorescence signal quenched by Fe3+, and then recovered by AA owing to releasing –NH2/–OH and introducing defects on SiCDs. The smartphone with an application named “AA-Tester” was established to analyze AA and exhibited high sensitivity with low detection limits of 18.12 nmol/L. HPLC method was used to verify the SPOC sensor and obtained satisfactory accuracy with relative standard deviations of 0.79–2.31 %. The portable sensing platform integrated fluorescence sensor with smartphone-device will be favorable for ultrasensitive and on-the-spot detection of AA.

An effective benzothiazole-indandione D-π-A fluorescent sensor for “ratiometric” detection of hydrazine: Its solvatochromism properties and applications in environmental samples and living cells

Hydrazine (N2H4) has high toxic impact and is widely used as raw material. As a result, it poses serious health risks and the following environmental pollution. Therefore, hydrazine's detecting techniques remains constantly under investigation. Herein, we report a ratiometric D-π-A fluorescent probe displaying NIR emission based on the ICT mechanism to detect N2H4. Other tested analytes have no observable interferences on the sensitivity and selectivity. The probe has sensitivity for N2H4 down to 1.29 μM with quick detection time (about 2.0 min). Moreover, the probe demonstrates solvatochromism with obvious emission varying from dull red to green, which implied high sensitivity to medium polarity. A portable smartphone platform for point-of-care detection of N2H4 in water samples is constructed. As a proof of real samples, the probe is successfully applied to sense N2H4 in water samples, to bioimage N2H4 in living cells and in plant cells with low cytotoxicity, suggesting significant potential application. This strategy opens up the preparation of new ratiometric fluorescence systems for bioimaging and environmental monitoring applications.

Multifunctional MnCo@C yolk-shell nanozymes with smartphone platform for rapid colorimetric analysis of total antioxidant capacity and phenolic compounds

Accurate on-site analysis of food quality, environmental pollutants, and disease biomarkers is of great significance for safeguarding public health. In this work, based on the novel nanozymes, MnCo oxides@carbon yolk-shell nanocages (MnCo@C NCs), a portable colorimetric sensor with smartphone platform has been developed for rapid, on-site and quantitative analysis of total antioxidant capacity (TAC) and phenolic compounds. The MnCo@C NCs are synthesized via one-step calcination of polydopamine-coated MnCo Prussian blue analogs (MnCo-PBA@PDA). The PDA-derived carbon shell is found to be able to protect the nanocages from collapsing, thus increasing their specific surface areas and porosity. Benefiting from the unique structure and multivalent MnCo bimetallic oxides, the MnCo@C NCs perform outstanding catalytic performance and multiple enzyme-mimicking activities including oxidase, laccase and catalase. Hence, a multifunctional application platform integrated smartphone has been constructed for rapid and sensitive colorimetric detection of three model analytes (i.e., ascorbic acid (AA), 2,4-dichlorophenol (2,4-DP), and epinephrine) with extremely low detection limits of 0.29 μM, 0.76 μM, and 0.70 μM, respectively. This sensor device is successfully applied in TAC analysis in vegetables, fruits, and beverages, as well as epinephrine determination in human serum samples. This work provides new insights into designing multifunctional nanozymes to advance the instant detection technology in the field of food supervision, environment monitoring, and human health.

Malware detection for Android application using Aquila optimizer and Hybrid LSTM-SVM classifier

INTRODUCTION: Android OS is the most recent used smartphone platform in the world that occupies about 80% in share market. In google play store, there are 3.48 million apps available for downloading. Unfortunately, the growth rate of malicious apps in google play store and third party app store has become a big concern, which holds back the development of the Android smartphone ecosystem. OBJECTIVES: In recent survey, a new malicious app has been introduced for every 10 seconds. These malicious apps are built to accomplish a variety of threats, such as Trojans, worms, exploits, and viruses. To overcome this issue, a new efficient and effective approach of malware detection for android application using Aquila optimizer and Hybrid LSTM-SVM classifier is designed. METHODS: In this paper, the optimal features are selected from the CSV file based on the prediction accuracy by cross validation using Aquila optimizer and the mean square error (MSE) obtained by the cross validation is consider as the fitness function for the Aquila to select the optimal features. RESULTS: The extracted optimal features are given to the Hybrid LSTM-SVM classifier for training and testing the features to predict the malware type in the android system. CONCLUSION: This proposed model is implemented on python 3.8 for performance metrics such as accuracy, precision, execution time, error, etc. The acquired accuracy for the proposed model is 97%, which is greater compared to the existing techniques such as LSTM, SVM, RF and NB. Thus, the proposed model instantly predicts the malware from the android application.

Utilizing Real-time Technology to Assess the Impact of Home Environmental Exposures on Asthma Symptoms: Protocol for an Observational Pilot Study.

BackgroundIt is estimated that over 60% of adults with asthma have uncontrolled symptoms, representing a substantial health and economic impact. The effects of the home environment and exposure to volatile organic compounds (VOCs) and fine particulate matter (PM2.5) on adults with asthma remain unknown. In addition, methods currently used to assess the home environment do not capture real-time data on potentially modifiable environmental exposures or their effect on asthma symptoms.ObjectiveThe aims of this study are to (1) determine the feasibility and usability of ecological momentary assessment (EMA) to assess self-report residential environmental exposures and asthma symptoms, home monitoring of objective environmental exposures (total VOCs and PM2.5), and lung function in terms of forced expiratory volume in 1 second (FEV1%); (2) assess the frequency and level of residential environmental exposures (eg, disinfectants/cleaners, secondhand smoke) via self-reported data and home monitoring objective measures; (3) assess the level of asthma control as indicated by self-reported asthma symptoms and lung function; and (4) explore associations of self-reported and objective measures of residential environmental exposures with self-reported and objective measures of asthma control.MethodsWe will recruit 50 adults with asthma who have completed our online Global COVID-19 Asthma Study, indicated willingness to be contacted for future studies, reported high use of disinfectant/cleaning products, and have asthma that is not well controlled. Participants will receive an indoor air quality monitor and a home spirometer to measure VOCs, PM2.5, and FEV1%, respectively. EMA data will be collected using a personal smartphone and EMA software platform. Participants will be sent scheduled and random EMA notifications to assess asthma symptoms, environmental exposures, lung function, and mitigation strategies. After the 14-day data collection period, participants will respond to survey items related to acceptability, appropriateness, and feasibility.ResultsThis study was funded in March 2021. We pilot tested our procedures and began recruitment in April 2022. The anticipated completion of the study is 2023.ConclusionsFindings from this feasibility study will support a powered study to address the impact of home environmental exposures on asthma symptoms and develop tailored, home-based asthma interventions that are responsive to the changing home environment and home routines.Trial RegistrationClinicalTrials.gov NCT05224076; https://clinicaltrials.gov/ct2/show/NCT05224076International Registered Report Identifier (IRRID)DERR1-10.2196/39887

Analisis Pengalaman Pengguna Pada Aplikasi TIX ID Menggunakan Metode User Experience Questionnaire

TIX ID is an online cinema ticket purchase application that plays on a smartphone platform. Where users can buy cinema tickets anywhere and anytime without having to wait in line. The concept of purchasing cinema tickets is integrated with a third party, namely DANA as a digital money concept that is integrated with several large applications such as Bukalapak and Ramayana. This study aims to determine the effect of service quality on TIX ID application users in ordering online cinema tickets. and want to know which user experience suits the user both in terms of comfort, function and customer convenience in using TIX ID supporting applications. This study provides a level of satisfaction through a User Experience Questionnaire (UEQ) which has six assessment aspects including attractiveness, perspicuity, efficiency, dependability, stimulation and novelty. The UEQ questionnaire was distributed to 55 respondents, the results of the UEQ questionnaire showed that respondents had a positive impression of the TIX ID application where the application showed a positive evaluation.

Decision-makers are more impulsive on smartphones than on computers

• Individuals have a higher present bias when they use a smartphone. • Individuals are less willing to invest time to obtain information when using a smartphone. • Decision makers are more impulsive on smartphones than computers. • A novel approach to study costly information search. Abstract 1 1 I acknowledge financial support from The Blavatnik Interdisciplinary Cyber Research Center. I want to thank Ayala Arad, Itai Ater, Shay Danziger , Dotan Persitz, Ariel Rubinstein, and Peter Zubcsek for helpful comments. As the use of smartphones becomes increasingly pervasive, the question arises as to whether the smartphone platform induces different choices than the computer platform. An incentivized-choice lab experiment is carried out to examine the effect of the smartphone environment on intertemporal decision-making and risky choices. In addition, a novel approach is introduced in order to study costly information search. While no significant differences are found between the platforms in the case of risky choices, there was significantly more present bias in the case of the smartphone platform than in the case of the computer platform. Furthermore, smartphone users were significantly less willing to invest time in order to obtain information that may increase their payoff. Overall, the findings suggest that decision makers exhibit more impulsive behavior on the smartphone platform relative to the computer platform.

Blue Carbon Dot-Based Portable Smartphone Platform for Visualization of Copper(II)

The acidic soil where tea grows makes the accumulation of copper ions (Cu2+) easy. Long-term drinking of tea infusions and tea beverages will cause abnormal accumulation of copper in the human body and endanger human health. Herein, we designed a visual portable smartphone platform based on ratiometric fluorescent nanoprobes for the rapid, real-time, and sensitive detection of Cu2+ in tea and tea beverages. We synthesized the ratiometric fluorescent nanoprobe formed by blue carbon dots (BCDs), which are used as internal standards, and a sensing reagent (diethyl-[5-(2-1,4,7,10-tetraaza-cyclododec-1-yl-acetylamino)-benzo[α]phenoxazin-9-ylidene]-ammonium (cyclen-NB)) for Cu2+. With an excitation wavelength of 330 nm, the emission wavelengths of cyclen-NB and BCDs are 674 and 451 nm, respectively. Cyclen-NB effectively captures Cu2+ to form a metal complex via a ligand-to-metal charge transfer (LMCT), resulting in obvious color changes from red to blue-violet. The designed ratiometric fluorescent nanoprobe has high sensitivity, good selectivity, and strong anti-interference ability, and the detection limit can be as low as 1.37 nM. Furthermore, a visual portable sensing platform was constructed based on the ratiometric fluorescent nanoprobe in combination with smartphones. The color recognition software of the smartphone can convert the color information of the photos taken by the mobile phone into digital data for analysis; and the detection limit is as low as 4.83 nM, and the yield rate is 86.79–111.20% (RSD ≤ 4.95). Therefore, the method reported in this manuscript can provide a convenient method for rapid on-site and visual inspection of tea and tea beverages for food safety.

A Novel Traffic Based Framework for Smartphone Security Analysis

Android Operating system (OS) has grown into the most predominant smartphone platform due to its flexibility and open source characteristics. Because of its openness, it has become prone to numerous attackers and malware designers who are constantly trying to elicit confidential information by articulating a plethora of attacks through these designed malwares. Detection of these malwares to protect the smartphone is the core function of the smartphone security analysis. This paper proposes a novel traffic-based framework that exploits the network traffic features to detect these malwares. Here, a unified feature (UF) is created by graph-based cross-diffusion of generated order and sparse matrices corresponding to the network traffic features. Generated unified feature is then given to three classifiers to get corresponding classifier scores. The robustness of the suggested framework when evaluated on the standard datasets outperforms contemporary techniques to achieve an average accuracy of 98.74 per cent.

MOBILE FATWA OF SELANGOR STATE DEPARTMENT OF MUFTI FROM THE ASPECT OF USER FRIENDLY

Fatwa is a reference for Muslims instead of Al-Quran, Hadith, ijma, and qiyas related to Fiqh that are not clearly described. It is issued by a group of scholars or those who have authority in the science of jurisprudence in Islam. In Malaysia, fatwas can only be gazetted by muftis appointed by king in each state or by ‘Yang Dipertuan Agung’ (king of the country). However, the gazetted fatwa was not utilized by the community for their guidance and reference. This application initiative called M-Fatwa that facilitate information on fatwas to be reached to the public. The content of the fatwa included in this application is taken from the Selangor State Mufti Department. It was developed using a smartphone platform and tested on users from various backgrounds to evaluate the effectiveness and usability of the app. There are about 350 respondents were involved in the study which consisted of users of the M-Fatwa application. The findings show that the application developed meets the needs of users and is suitable for reference.