Android Tool Research Articles

Design of the Android-Based Malaria-Mapping Application Mobfabria

Malaria represents one of the tropical diseases and a health problem in the East Nusa Tenggara (NTT) Province. Malaria cases are still high in some districts in NTT, including East Sumba, Central Sumba, West Sumba, and Southwest Sumba. Infants, children, and pregnant women are the high-risk groups to suffer from malaria. The highest number of cases was recorded in Southwest Sumba district with 4,273 cases in November 2022. This situation requires preventive and curative actions to address malaria cases in NTT. These actions include health education and malaria data mapping for high-risk groups in malaria-endemic areas. It is expected that these measures will assist in healthcare services, especially in malaria-endemic areas. Considering the current phenomenon of digital era development, the researchers have designed an Android-based mapping and education application for malaria called “mobfabria”. To develop a prototype of the mobfabria applicatio. This is research and development study. The research was conducted in 2023, where the application test took place from March to April 2023 at the Oemasi Health Center in Kupang District. The research subjects consisted of 5 individuals during the development stage and 15 pregnant women during the evaluation stage. The application created by the researchers can be downloaded from the Play Store: https://play.google.com/store/apps/details?id=com.mobfabria.apps. The research stages are approval, ethical test, instrument test, and application test. The application is developed according to the needs analysis, system design, and database. It was built using Android tools. The assessment by experts in health promotion, media, and malaria practitioners was considered good enough, leading to changes in the application's interface design and data storage units. The data was analyzed descriptively. Mapping and data collection of pregnant women with malaria can be accurately obtained. This application is expected to be used for healthcare services and facilities in malaria-endemic areas.

Blockchain Based e-Voting System

Abstract: There may be no doubt that the progressive idea of the blockchain, that is the underlying era in the back of the famous cryptocurrency Bitcoin and its successors, is triggering the beginning of a brand new generation in the net and the web services. At the same time as most people focus simplest at cryptocurrencies; in truth, many administrative operations, fintech techniques, and regular services that may handiest be finished offline and/or in person, can now competently be moved to the net as on-line offerings. What makes it a powerful tool for digitizing everyday services is the creation of clever contracts, as in the Ethereum platform. Smart contracts are meaningful portions of codes, to be integrated in the blockchain and achieved as scheduled in each step of blockchain updates. E-voting on the other hand, is every other trending, yet vital, subject matter related to the online services. The blockchain with the smart contracts, emerges as an excellent candidate to apply in trends of more secure, less expensive, more comfortable, more obvious, and less complicated-to-use e vote casting systems. Ethereum and its community is one of the most suitable ones, due to its consistency, full-size use, and provision of smart contracts common sense. An e-balloting system should be comfy, as it has to now not allow duplicate votes and be completely obvious, at the same time as shielding the privacy of the attendees. In this work, we have carried out and tested a sample e-vote casting utility as a smart settlement for the Ethereum community, the use of the Ethereum wallets and the Solidity language. Android platform is likewise taken into consideration to permit vote casting for individuals who do not have an Ethereum wallet. After an election is held, eventually, the Ethereum blockchain will maintain the facts of ballots and votes. customers can submit their votes through an Android tool or immediately from their Ethereum wallets, and those transaction requests are treated with the consensus of each unmarried Ethereum node. This consensus creates a transparent environment for e-balloting. similarly to a large dialogue about reliability and performance of the blockchain-based e vote casting structures, our application and its take a look at consequences are presented on this paper, too.boundaries. Keywords: E-voting, Smart-contracts, Blockchain, Ethereum

Autonomous Surveillance of Infants’ Needs Using CNN Model for Audio Cry Classification

Infants portray suggestive unique cries while sick, having belly pain, discomfort, tiredness, attention and desire for a change of diapers among other needs. There exists limited knowledge in accessing the infants’ needs as they only relay information through suggestive cries. Many teenagers tend to give birth at an early age, thereby exposing them to be the key monitors of their own babies. They tend not to have sufficient skills in monitoring the infant’s dire needs, more so during the early stages of infant development. Artificial intelligence has shown promising efficient predictive analytics from supervised, and unsupervised to reinforcement learning models. This study, therefore, seeks to develop an android app that could be used to discriminate the infant audio cries by leveraging the strength of convolution neural networks as a classifier model. Audio analytics from many kinds of literature is an untapped area by researchers as it’s attributed to messy and huge data generation. This study, therefore, strongly leverages convolution neural networks, a deep learning model that is capable of handling more than one-dimensional datasets. To achieve this, the audio data in form of a wave was converted to images through Mel spectrum frequencies which were classified using the computer vision CNN model. The Librosa library was used to convert the audio to Mel spectrum which was then presented as pixels serving as the input for classifying the audio classes such as sick, burping, tired, and hungry. The study goal was to incorporate the model as an android tool that can be utilized at the domestic level and hospital facilities for surveillance of the infant’s health and social needs status all time round.

SMS Observer: A dynamic mechanism to analyze the behavior of SMS-based malware

Nowadays smartphones become an indispensable tool in many people's everyday life that makes themselves attractive targets for attackers. Among various malware targeting at smartphones, SMS-based malware is one of the most notorious ones. Though a number of Android dynamic analysis frameworks have been proposed to analyze SMS-based malware, most of these frameworks or some Android tools, such as Google Android Emulator, do not support an app or malware to send SMS messages to a real smartphone; hence, security researchers cannot use them directly to analyze the behavior of SMS-based malware. In our previous work, SMS Helper, we designed an application layer tool to allow an app or malware in an Android emulator to send and receive SMS messages to or from a real smartphone. Based on SMS Helper, this paper proposes an Android dynamic analysis framework, called SMS Observer, to assist security researchers to analyze SMS-based malware. SMS Observer integrates SMS Helper into it as a client agent, meanwhile, and it maintains the integrity of system logs. This paper also figures out a way to detect whether an app is executed in an emulator and describes how to use SMS Observer to prevent such evasion. Experimental results using real-world malware samples show SMS Observer is much more effective in detecting SMS-related behavior of SMS-based malware than existing frameworks, such as Google Android Emulator, Andrubis, CopperDroid, and DroidBox. SMS Observer can analyze sophisticated SMS-based malware samples and provide a comprehensive view of malicious behavior.

A mobile android tool for simplified GPR data processing in construction applications

Abstract This work presents a new GPR signal processing tool for mobile devices, which uses the free Android platform in smartphones and tablets. The developed application is able to display and process radargrams without using the most common commercial software applied for GPR signal processing. These existing applications have usually been developed for advanced signal processing, which results in complex processes and requires large computational resources. Therefore, the aim of this work was to develop a simplified and intuitive tool, which allows speeding up the GPR signal processing. For such purpose, the application implements basic filters to optimize the GPR images analysis and to facilitate data interpretation. Different tools have also been implemented to obtain interesting geometric measurements, such as thicknesses and diameters in rebar or piping. Thus, any non-expert user on the GPR technique could generate preliminary in-situ results using conventional smartphone or tablet devices.

AN ARCHITECTURE-BASED TECHNIQUE TO MOBILE CONTACT RECOMMENDATION FOR EMERGENCY SITUATION IN NIGERIA

Smart technologies such as smart phones, iPad and Tablets are ubiquitous in today’s society. They possess increasing computing and storage potentials. Thus, emerging as a dominant computing platform for different kinds of end-users. However, these technological possibilities have not been fully explored for emergency situations where close relatives must be contacted. This paper therefore presents an Emergency Contact Recommendation Model (ECRM) that was implemented into an emergency contact recommendation system. An architectural based approach was employed to highlight the contribution this paper made to extant knowledge. The leveraged of the Dust miner algorithmic technique, the direct discriminative pattern mining, and the Bayesian Inference Network technique were used to formulate the ECRM. The ECRM was implemented using the Java development and android tool kit. The model demonstrated commendable capabilities - considering the foregoing techniques when compared with what obtains in literature- to make useful recommendation in emergency situation(s) after implementation. http://dx.doi.org/10.4314/njt.v36i124

AN ARCHITECTURE-BASED TECHNIQUE TO MOBILE CONTACT RECOMMENDATION FOR EMERGENCY SITUATION IN NIGERIA

Smart technologies such as smart phones, iPad and Tablets are ubiquitous in today’s society. They possess increasing computing and storage potentials. Thus, emerging as a dominant computing platform for different kinds of end-users. However, these technological possibilities have not been fully explored for emergency situations where close relatives must be contacted. This paper therefore presents an Emergency Contact Recommendation Model (ECRM) that was implemented into an emergency contact recommendation system. An architectural based approach was employed to highlight the contribution this paper made to extant knowledge. The leveraged of the Dust miner algorithmic technique, the direct discriminative pattern mining, and the Bayesian Inference Network technique were used to formulate the ECRM. The ECRM was implemented using the Java development and android tool kit. The model demonstrated commendable capabilities - considering the foregoing techniques when compared with what obtains in literature- to make useful recommendation in emergency situation(s) after implementation. http://dx.doi.org/10.4314/njt.v36i124

Recording, storing and querying judo match data using an Android tool and Cloud computing

Judo is a martial art that was created as a physical, intellectual and moral education method in Japan. In competition matches, Judo is a combat sport where two athletes fight against each other. Judo matches are ruled by different scores, penalties and durations, which change regarding the age and gender of the competitors. There is a need to record the actions in favour of or against a judoka during a match in order to create an efficient training programme as well as technical and tactical development strategies for each competitor. In this work, a technological solution is presented; it records each athlete’s matches and scores, penalties, pauses during the match and its actual length of time. These aspects can help to create charts reflecting efforts made by the judoka. The research is focused on the support of the technical–tactical analysis of judo matches, taking into account recent information technology and communications trends: (1) the solution is developed for mobile devices which use the Android operating system, (2) the solution takes advantage of Cloud computing to allow ubiquitous access to the data and (3) the desktop component of the solution is portable to many computer systems because it has been developed using the Java programming language. The initial results show how the technological solution can be used for improving the performance of the athlete by providing feedback of the behaviour of the judoka during each match.

System Call Analysis of Android Malware Families

Background/Objectives: Now a days, Android Malware is coded so wisely that it has become very difficult to detect them. The static analysis of malicious code is not enough for detection of malware as this malware hides its method call in encrypted form or it can install the method at runtime. The system call tracing is an effective dynamic analysis technique for detecting malware as it can analyze the malware at the run time. Moreover, this technique does not require the application code for malware detection. Thus, this can detect that android malware also which are difficult to detect with static analysis of code. As Android was launched in 2008, so there were fewer studies available regarding the behavior of Android Malware Families and their characteristics. The aim of this work is to explore the behavior of 10 popular Android Malware Families focused on System Call Pattern of these families. Methods/Statistical Analysis: For this purpose, the authors have extracted the system call trace of 345 malicious applications from 10 Android Malware Families named FakeInstaller, Opfake, Plankton, DroidKungFu, BaseBridge, Iconosys, Kmin, Adrd and Gappusin using strace android tool and compared it with the system calls pattern of 300 Benign Applications to justify the behavior of malicious application. Findings: During the experiment, it is observed that the malicious applications invoke some system calls more frequently than benign applications. Different Android malware invokes the different set of system calls with different frequency. Applications/Improvements: This analysis can prove helpful in designing intrusion-detection systems for an android mobile device with more accuracy.

Implement of Face Recognition in Android Platform by Using Opencv and LBT Algorithm

One way of consideration for identifying the human IS recognition of face by portable tools like mobile and tablet. One challenge is low power in portable android tools for face recognition (identification), so GPU must be used in software connection central Graphic processor which has a good function, compared to present processors in today portable android tools. Binary pattern (local) is one of the methods that are used for characteristic production and the image stratification. In this study, it is suggested to use connection and local binary pattern histogram algorithm to use optimum software open CV and using hardware platform android to identify the face.

M-STEPS: Developing and implementing a smart innovative android tool for noncommunicable disease risk factor (STEPS) survey in India

m-STEPS: Developing and implementing a smart innovative android tool for noncommunicable disease risk factor (STEPS) survey in India