Proposed approaches for intelligent classification of mobile apps for smart phones

2014 ◽  
Author(s):  
Marwan Alseid ◽  
Jawad H AlKhateeb ◽  
Obaidah A. Rawashdeh
Keyword(s):  
Mobile Apps ◽  
Smart Phones

India Goes Digital..Smartphone is the New Shopping Destination

2018 ◽  
Vol 6 (8) ◽  
pp. 289
Author(s):  
Shankar Chaudhary
Keyword(s):  
Online Shopping ◽  
Mobile Apps ◽  
Smart Phone ◽  
Mobile Commerce ◽  
Mobile App ◽  
Smart Phones ◽  
The Internet ◽  
The World ◽  
Shopping Experience ◽  
User Friendly

Despite being in nascent stage m-commerce is gaining momentum in India. The explosive growth of smart-phone users has made India much loved business destination for whole world. Indian internet user is becoming the second largest in the world next to China surpassing US, which throws open plenty of e-commerce opportunities, not only for Indian players, offshore players as well. Mobile commerce is likely to overtake e-commerce in the next few years, spurred by the continued uptrend in online shopping and increasing use of mobile apps.The optimism comes from the fact that people accessing the Internet through their mobiles had jumped 33 per cent in 2014 to 173 million and is expected to grow 21 per cent year-on-year till 2019 to touch 457 million. e-Commerce brands are eyeing on the mobile app segment by developing user-friendly and secure mobile apps offering a risk-free and easy shopping experience to its users. Budget 4G smart phones coupled with affordable plans, can very well drive 4G growth in India.

Secure Examination Management System for M-Learning (SEMS)

2017 ◽  
Vol 2 (2) ◽  
pp. 31-35
Author(s):  
Akshada Abnave ◽  
Charulata Banait ◽  
Mrunalini Chopade ◽  
Supriya Godalkar ◽  
Soudamini Pawar ◽  
...  
Keyword(s):  
Face Recognition ◽  
Social Interactions ◽  
Mobile Devices ◽  
Management System ◽  
Mobile Apps ◽  
Smart Phones ◽  
Examination System ◽  
Open Environment ◽  
Exchange Information ◽  
Personal Mobile Devices

M-learning or mobile learning is defined as learning through mobile apps, social interactions and online educational hubs via Internet or network using personal mobile devices such as tablets and smart phones. However, in such open environment examination security is most challenging task as students can exchange mobile devices or also can exchange information through network during examination. This paper aims to design secure examination management system for m- learning and provide appropriate mechanism for anti- impersonation to ensure examination security. The users are authenticated through OTP. To prevent students from exchanging mobile devices during examination, system re-authenticates students automatically through face recognition at random time without interrupting the test. The system also provides external click management i.e. prevent students from accessing online sites and already downloaded files during examination.

scholarly journals The Effectiveness of Branded Mobile Apps on User’s Brand Attitudes and Purchase Intentions

2016 ◽  
Vol 9 (1) ◽  
pp. 141-154 ◽  
Author(s):  
Victoria A. Seitz ◽  
Nada M. Aldebasi
Keyword(s):  
United States ◽  
Correlation Analysis ◽  
Mobile Device ◽  
Mobile Apps ◽  
The United States ◽  
Purchase Intentions ◽  
Smart Phones ◽  
Brand Attitudes ◽  
Limited Impact ◽  
The Past

AbstractThe mobile device market, particularly for smart phones, has experienced incredible growth over the past five years. What sets this market apart is the use of applications or apps for just about anything from information to purchases. The purpose of the study was to examine the effectiveness of branded apps on consumers’ attitudes toward brands as well as purchase intentions. The sample was drawn from students enrolled at a southwestern university in the United States, resulting in 50 usable questionnaires. Results of Pearson’s correlation analysis indicated that using branded apps strongly influenced users’ attitudes toward brands; however, using branded apps had a smaller impact on purchase intentions. As well, attitudes towards the branded apps, although significant, had a limited impact on purchase intentions. Implications of the findings were then discussed.

scholarly journals Customer Segmentation Through Path Reconstruction

2020 ◽  
Author(s):  
Santiago García
Keyword(s):  
Rapid Development ◽  
Customer Segmentation ◽  
Smart Phones ◽  
Indoor Environments ◽  
Flow Conditions ◽  
Gps Receivers ◽  
Current State ◽  
Different Types

With the rapid development of smart phones, tablets and their operative systems, many positioning enabled sensors have been built into these devices. Users can now accurately fix their location according to the function of GPS receivers. For indoor environments, as in the case we are studying, WiFi based positioning is preferred to GPS due to the attenuation or obstruction of signals. This paper deals with the automatic classification of customers in a Sports Shop Center on the basis of their movements around the shop's premises. To achieve this goal, we start by collecting (x,y) coordinates from customers while they visit the store. Consequently, any costumer's path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. Then, a guess about the full trajectory is constructed and a number of parameters about these trajectories is calculated before performing an Unsupervised Learning Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. This information is of great value to the company, to be used both in the long term and also in short periods of time, monitoring the current state of the shop at any moment, identifying different types of situation appearing during restricted periods, or predicting customer flow conditions

scholarly journals Android Application Development

2021 ◽  
Vol 9 (VI) ◽  
pp. 3188-3192
Author(s):  
Ritu Sharma
Keyword(s):  
Operating System ◽  
Digital Media ◽  
Operating Systems ◽  
Mobile Apps ◽  
Video Recording ◽  
Weather Forecast ◽  
Smart Phones ◽  
Human Beings ◽  
Application Development ◽  
Audio Video

Technology is being used and improved by human beings over a long period of time now and Smartphones is one of them. Smart Phones contain touch screen, built in keyboard, high resolution camera, front side camera for video conferencing, etc. They are used for making and receiving calls, sending and receiving messages, accessing the Internet, digital media, incorporating audio/video recording etc. Different smart phones have different operating systems and mobile applications are developed for each operating system in smart phones, tablet or mobile phones, in order to serve the needs of the user. These apps are either preinstalled or downloadable from online app market that can do almost everything. Apps make a mobile be like a portable computer having multi core processors, gigabytes of memory and a real operating system. Originally mobile apps were made available for only calling, messaging and informational purposes like calendar, weather forecast, e- mail, etc. With improvement in technology and increase in user demands, developers started making apps for other purposes like games, banking, video chats etc. Some apps are also used to present data in the same format as on a computer website and also allow you to download content that you can use when there is no Internet. There are many apps available in market today for different Operating Systems in which Android is having the maximum market share these days.

Cybersecurity for Smart Phones, Mobile Apps, and “The Cloud”

2015 ◽  
pp. 83-101
Author(s):  
Joseph N. Pelton ◽  
Indu B. Singh
Keyword(s):  
Mobile Apps ◽  
Smart Phones

scholarly journals How organic is organic milk? Can we have a quick check?

NIR news ◽  
2019 ◽  
Vol 30 (2) ◽  
pp. 18-21 ◽  
Author(s):  
Saskia van Ruth ◽  
Ningjing Liu
Keyword(s):  
Smart Phones ◽  
Organic Milk ◽  
Organic Product ◽  
Near Future

The organic market is growing, and confidence is key. However, it is hard to distinguish an organic product from another regular product. In this article we examined a consumer NIRS-Vis device for its capabilities to distinguish organic retail milks from conventional milks. The study revealed differences between the two groups, allowing classification of samples, but these differences were not as distinct as those provided by other devices examined previously. Nevertheless, with some improvement of performance of this kind of devices and integration in smart phones, authentication of foods is within reach of citizens in the near future.

scholarly journals Technical Setbacks Encountered in Internet Based Travel Booking Applications

2019 ◽  
Vol 9 (2S4) ◽  
pp. 175-177
Keyword(s):  
Data Analysis ◽  
Key Words ◽  
Service Industry ◽  
Mobile Apps ◽  
Smart Phones ◽  
Chi Square ◽  
Continuous Growth ◽  
Multiple Devices ◽  
Major Factors

This study aims at identifying the factors which influence the customers to use cab apps. Due to the continuous growth and usage of internet and smart phones the service industry has widened their services through online mobile apps. Some major factors are identified through this study and anova and chi-square are used for data analysis. It is found from the study that consumers are mostly influenced by advanced booking technology and view on multiple devices. (Key words: convenience, advanced booking, cab apps, view on multiple devices)..

scholarly journals Technologies in the education of children and teenagers with autism: evaluation and classification of apps by work areas

2021 ◽  
Author(s):  
Carmen del Pilar Gallardo-Montes ◽  
María Jesús Caurcel Cara ◽  
Antonio Rodríguez Fuentes
Keyword(s):  
Executive Functions ◽  
Time Management ◽  
Mobile Apps ◽  
Children With Autism ◽  
Work Area ◽  
Recorded Data ◽  
Correlation Statistics ◽  
Content Design ◽  
Google Play

AbstractMobile apps represent a resource with great potential for encouraging the development of many skills, given the high number of apps available and the quick access to them. Many professionals and families include these resources in the education and therapy of children with autism. For a group with such particular needs, a review of the apps is great importance, since, due to their characteristics, the apps must provide content, design and pedagogical aspects that fit those needs. Through a previously validated system of indicators, 155 free apps on Google Play were evaluated, using “autism” in English and in Spanish. We determined which work area each app developed, as well as which were the most multifaceted. Having evaluated the recorded data, we calculated frequencies, percentages and reliability, as well as parametric contrast and correlation statistics. We found that the focus of most apps was on executive functions, language and entertainment, with a minority devoted to the emotional sphere or time management. However, 98.06% of the apps worked on several areas, which makes them more functional but with the downside of not being specialized. Most apps were placed in the “recommendable” level but with margin for improvement in increasing their functionality.

scholarly journals Classification of Activities of Daily living using Smart Phones

2019 ◽  
Vol 8 (3) ◽  
pp. 2984-2988
Keyword(s):  
Activities Of Daily Living ◽  
Daily Living ◽  
Human Life ◽  
Smart Phone ◽  
Smart Phones ◽  
Machine Learning Techniques ◽  
Accelerometer Sensor ◽  
Learning Techniques ◽  
Direct Input

Smart phones have become an integral part of everyday human life. These phones are packed with various sensors for different purposes. Most of them are used for understanding the environment in which the user uses the phone so that the device could respond rapidly. Indirectly the phone extracts context information of the users like the activity performed using accelerometer and gyroscope sensors. This information can be used for a variety of applications like home automation, smart environment, etc to perform automatic changes to the environment without direct input from the user. This paper deals with the classification of activities of daily living like walking, jogging, sitting, standing, upstairs and downstairs using the data collected from accelerometer sensor within the smart phone. A comparative analysis has been performed on different machine learning techniques for activity classification.

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