Application for Party Based on Cloud Platform

Android applications are considered the most popular and desirable applications due to their friendly interface, various categories and available options, and supporting most of the available hardware in the market. Complexity to understand, design, develop, implement, and test android applications have been raised. Maintainability is a very important quality attribute that we should consider it seriously. However, it is one of the most difficult and costly attributes that can be achieved. The software metrics are used to predict and estimate the software maintainability value. There are several metrics and formulas that are used to measure and estimate the maintainability value. These metrics and formulas are derived from the different usages of the maintainability. This paper focus on analyzing and measuring the maintainability of Android mobile applications using Object Oriented metrics and Android Metrics. The purpose of this paper is to assess the impact all of these metrics on the maintainability of Android applications and choose the metrics that has the highest impact.

Android access control granularity based on its permission mechanism is relatively coarse, which cannot effectively protect the user privacy. Many Android applications do not strictly abide by the principle of least privilege (PLP). Both benign and malicious apps may request more permissions than those they really use. We rethink previous permission over-claim problem of Android applications, and extend it to three kinds of problems: Explicit Permission Over-claim, Implicit Permission Over-claim and Ad Library Permission Over-claim. The latter two problems are new that have not been raised by any previous work. Static analysis is to decompile the applications to generate intermediate code and then analyze the usage of permissions. Our static analysis on 10710 applications shows that 76.08% of them may have Explicit Permission Over-claim problem, among those there are 424 applications that have sensitive permissions, which are only used in the advertisement library’s code of the applications rather than developer’s own code. They have Ad Library Permission Over-claim problem. The main idea of our semantic analysis is to calculate the semantic similarity between apps’ descriptions and function phrases. If the similarity exceeds a certain threshold, the app is considered relevant to the corresponding function. We compare the results of the semantic analysis with those of manual reading of 102 Android application descriptions. The F-measures of the three chosen functions are 80.82%, 70.48% and 89.62%, respectively. The evaluation results show our method can efficiently detect the above three kinds of permission over claim problems which indicates that our method would be helpful for normal users to have a clear understanding of permission usage of Android applications.

With the development of Internet technology, social media short video plays a more and more important role in people's daily life. In addition to bringing joy to people, short videos can also bring certain knowledge and skills. In recent years, people pay more and more attention to the negative impact of indulging in short video. This paper mainly discusses the reasons of indulging in short video and its specific impact on people's life through quantitative research in the form of questionnaire survey. Through the cross analysis of 400 samples, this paper finds that the interactivity of social media comments and accurate algorithms enhance people's addiction to short videos. The vast majority of people are addicted to short videos, which is more serious for women than men. At the same time, different genders and occupations also show significant differences in the content of indulging in short videos. This study will be beneficial to provide new research questions and samples for social media research, and will also provide some suggestions and inspiration for short video operation.

ABSTRACTThe increasing use of smartphone technology in people's daily lives and its continuous development lead to the inevitable use of mobile applications because of their easy access anytime and anywhere. In this study, a new Android application for smartphones is developed and presented for the remote control of a micro‐cogeneration system from a mobile device without the need to be near the system. The mobile application consists of five different windows through which real‐time data on the most important variables of the system can be observed at any time. Additionally, the application allows the user to select the system's desired operating mode among a total of five possibilities. Alarms and warnings are also shown along with the detailed status of the main variables of the groups forming the system. Moreover, the application can graphically show the progression of variables at any time, and a history of the changes to the system is available. An experimental practice based on the “use of current mobile applications” for a subject of the Master of Thermal Engineering is proposed as a pedagogical method that involves the procedure “learning by doing,” in which students can realize the great advantages of using these technologies. © 2016 Wiley Periodicals, Inc. Comput Appl Eng Educ 24:497–507, 2016; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.21726

Purpose The purposes of this study were, first, to (re)design the user-interface of the activity tracker known as the MOX with the help of input from elderly individuals living independently and, second, to assess the use of and experiences with the adapted Measure It Super Simple (MISS) activity tracker in daily life. Methods The double diamond method, which was used to (re)design the user-interface, consists of four phases: discover, define, develop, and deliver. As a departure point, this study used a list of general design requirements that facilitate the development of technology for the elderly. Usage and experiences were assessed through interviews after elderly individuals had used the activity tracker for 2 weeks. Results In co-creation with thirty-five elderly individuals (65 to 89-years-old) the design, feedback system, and application were further developed into a user-friendly interface: the Measure It Super Simple (MISS) activity. Twenty-eight elderly individuals (65 to 78-years-old) reported that they found the MISS activity easy to use, needed limited help when setting the tracker up, and required limited assistance when using it during their daily lives. Conclusions This study offers a generic structured methodology and a list of design requirements to adapt the interface of an existing activity tracker consistent with the skills and needs of the elderly. The MISS activity seemed to be successfully (re)designed, like the elderly who participated in this pilot study reported that anyone should be able to use it. IMPLICATIONS FOR REHABILITATION This study provides an overview of important characteristics of the activity tracker interface for elderly individuals that can be used when choosing an appropriate activity tracker. This study can serve as a model that demonstrates how to adapt other eHealth and mHealth tools to improve the user-centred design. The MISS activity seems to be an elderly-friendly activity tracker that can facilitate a meaningful experience.

With the rapid growth of biological technology, large amount of biological data can be produced in few days or months. Many of common-used tools become computation-consuming in analyzing such big biological data. Cloud computing has emerged to provide the huge amount of computing power and play important role in development of bioinformatics tools. We propose a cloud computing framework that is able to easily deploy the bioinformatics tools on cloud virtualization platform based on Hadoop. This framework can work on the public cloud platform vendor such as Amazon EC2 and also private cloud platform. All the tools performed by cloud computing framework as Bioinformatics as a Services are available at http://bioinfo.cs.pu.edu.tw/CBBTS. The tools deployed on cloud platform by the proposed framework are tested in Providence University cloud platform and provided good proportional acceleration when scaled out onto many computational units. In the big biological data era, cloud computing based solutions are important role to develop bioinformatics services over internet. In the work, the proposed framework is able to simply deploy several well-known bioinformatics tools on cloud virtualization platform and as web services. This framework can work on the public cloud platform vendor such as Amazon EC2 and also private cloud platform.

We know the values or preferences of each member of a certain group, and we would like to know the values or preferences of the group as a whole. At the very least we would like to be able to entertain an educated opinion on what they ought to be. It is understood that the collective values or preference depend on the values or preferences of the members in such a way that each member is accorded the influence that is due to him. This is what we call an aggregation problem. Its structure is this: Given a set I of indices and a set of values with respect to these indices, find the value of I as a whole in such a way that a set C of conditions is satisfied. In the case just described the elements of I are individuals, alive at the same time and usually linked to each other in some interesting way. This case is well known and has been studied by moral philosophers and group decision theorists, before Arrow and after him. But other interpretations of the abstract problem are possible. Suppose for example that the elements of I are ordered pairs (i, t) where i is some fixed entity (society, group, individual, .. .) and t is a moment of time. Another kind of problem then arises. Formally it is somewhat different from the preceding one, for now I is a linear order with certain properties; in particular, I might be infinite. This kind of problem would seem to be as important as the problems associated with Kenneth J. Arrow's name. It is this family of problems that is referred to in the title of the paper, and we shall try to say something about it here. While our discussion does not concern ethical problems in our daily life, we feel that it has foundational interest. Roughly

Abstract: The Android application that can identify older people who may fall. Android is an operating system that Anyone can easily construct their own application on an open source platform. Families and medical experts are often concerned about older people falling. According to experts, falls are the seventh rank for death cause in the US. Adults 68 and older who fall untreated run the risk of major health problems because 21% of falls necessitate emergency medical attention and 11% of falls will result in the fractures. This is the rationale for the creation of a system for the elderly that can detect falls and alert the caregiver. The software keeps tabs on the person and notifies the caregiver if anything is wrong. This Android app's ability to send alarm messages to the caregiver with the necessary information is one of its important features. Important details like their geolocation and directions are included in the alert messages. The individual has the authority to put an end to a false alarm before taking any further action. This project is to help the elderly. Through a user-friendly interface, the smartphone application can spot possible falls and provide alerts to families, doctors, and other caregivers.

Wearable damaged clothing fabric image recognition system based on image restoration algorithm

Big data privacy preservation is one of the most disturbed issues in current industry. Sometimes the data privacy problems never identified when input data is published on cloud environment. Data privacy preservation in hadoop deals in hiding and publishing input dataset to the distributed environment. In this paper investigate the problem of big data anonymization for privacy preservation from the perspectives of scalability and time factor etc. At present, many cloud applications with big data anonymization faces the same kind of problems. For recovering this kind of problems, here introduced a data anonymization algorithm called Two Phase Top-Down Specialization (TPTDS) algorithm that is implemented in hadoop. For the data anonymization-45,222 records of adults information with 15 attribute values was taken as the input big data. With the help of multidimensional anonymization in map reduce framework, here implemented proposed Two-Phase Top-Down Specialization anonymization algorithm in hadoop and it will increases the efficiency on the big data processing system. By conducting experiment in both one dimensional and multidimensional map reduce framework with Two Phase Top-Down Specialization algorithm on hadoop, the better result shown in multidimensional anonymization on input adult dataset. Data sets is generalized in a top-down manner and the better result was shown in multidimensional map reduce framework by the better IGPL values generated by the algorithm. The anonymization was performed with specialization operation on taxonomy tree. The experiment shows that the solutions improves the IGPL values, anonymity parameter and decreases the execution time of big data privacy preservation by compared to the existing algorithm. This experimental result will leads to great application to the distributed environment.

The Spinal Cord Injury Spasticity Evaluation Tool: Development and Evaluation

Seniors tend to self-track their health in various ways in their daily life. In fact self-tracking has become a habit of their daily lives and a way of living. Therefore, Quantified-Self offers a great match for this age group in particular. Towards this direction we have been developing a web application which visualizes sensor data gathered in real-life settings for over a six-months' period. Technological details of the application developed are provided along with the type of visualized information. Further work is planned towards a user-friendly interface and the pilot testing of the application within the network of established living environments.

With the increasing popularity of the Android platform, we have seen the rapid growth of malicious Android applications recently. Considering that the heavy use of applications on mobile phones such as games, emails, and social network services has become a crucial part of our daily life, we have become more vulnerable to malicious applications running on mobile devices. To alleviate this hostile environment of Android mobile applications, we propose a malware detection approach that (1) extracts both built-in permissions and custom permissions requested by Android apps from their Manifest.xml and (2) applies the permissions and a Random Forest classifier to Android applications for classifying them into benign and malicious. The Random Forest classifier learns a model using the permissions to classify the input dataset of 45,311 Android applications. In the learned model, an optimal subset of permissions has been identified and then using the subset of permissions we could achieve 94.23% accuracy in detecting malware.

Atrial fibrillation (AF) is the most common arrythmia and is associated with costly morbidity such as stroke and heart failure. Mobile health (mHealth) has potential to help bridge the gaps of traditional healthcare models that may be poorly suited to the sporadic nature of AF. The Self-management and Educational technology support Tool for AF patients (SETAF) was designed based on the preferences and needs of AF patients but more study is required to assess the acceptance of this novel tool. Explore the usability and acceptance of SETAF among AF patients in Singapore. A mixed methods study was conducted with AF patients who were purposively sampled from an outpatient cardiology clinic in Singapore. After 6 weeks of using SETAF, semi-structured interviews were performed, and data were analyzed inductively following a thematic analysis approach. Results from a short 4-item survey and application usage data were also analyzed descriptively. Both qualitative and quantitative results were organized and presented following the Technology Acceptance Model (TAM) framework. A total of 37 patients participated in the study and 19 were interviewed. Participants perceived SETAF as useful for improving AF knowledge, self-management and access to healthcare providers and was easy to use due to the guided tutorial and user-friendly interface. They also identified the need for better personalization of content, psychosocial support features and reduction of language barriers. Application usage data revealed preference for AF related content and decreased interaction with the motivational message component of SETAF over time. Overall, most of the participants would continue using SETAF and were willing to pay for it. AF patients in Singapore found SETAF useful and acceptable as a tool for AF management. The insights from this study not only support the potential of mHealth but may also inform the design and implementation of future mHealth tools for AF patients.

Controlling the electronic devices through the Internet of Things (IoT) interfaces is essential in our mundane life. By observing the important parameters, controlling of the system can be performed which produces important pieces of information by keeping in mind the functioning of these e-devices. The outcomes of the environmental observances are associated with this scrutiny. The collected information can be used to create actions such as heating of devices, dominant cooling, or long-term statistics. Through the help of network or any other android application, data can be uploaded on the cloud. In the present study, Arduino UNO and Wi-Fi modules are used to process and transfer the sensed data to the Thingspeak cloud. Thus, the cloud platform (Thingspeak) contains the parameters that are received. Any variation in the surroundings is reported in the form of a database through the cloud computing method.