Search

Due to lack of a central bureaucrat in mobile ad hoc networks, the security of the network becomes serious issue. During malicious attacks, according to the motivation of intruder the severity of the threat varies. It may lead to loss of data, energy or throughput. This paper proposes a lightweight Intruder Node Detection and Isolation Action mechanism (INDIA) using feature extraction, feature optimization and classification techniques. The indirect and direct trust features are extracted from each node and the total trust feature is computed by combining them. The trust features are extracted from each node of MANET and these features are optimized using Particle Swarm Optimization (PSO) algorithm as feature optimization technique. These optimized feature sets are then classified using Neural Networks (NN) classifier which identifies the intruder node. The performance of the proposed methodology is studied in terms of various parameters such as success rate in packet delivery, delay in communication and the amount of energy consumption for identifying and isolating the intruder. [ABSTRACT FROM AUTHOR]

Mobile phones are becoming a communication tool commonly used by people all over the world; and they are started to be adopted in psychosocial therapies involving vulnerable people. We are herein presenting the results of an academic literature review. We identified scientific papers published between 2006 and 2015 resorting to academic databases available on the Internet, applying a systematic selection method based on quality criteria. Secondly, we analysed contents, highlighting the scarcity of research involving vulnerable people. The available literature specialized in psychosocial therapies offers investigation results which involve mobile phones and patients in general, focusing particularly on the clinical psychology field and, to a lesser extent, on the social work field. Particularly significant are the investigation works developed in the United States. In the present paper we introduce a first 'state of the art', identifying opportunities and also the limitations surrounding the use of mobile phones in psychosocial therapies targeting the vulnerable. Issues concerning privacy and data confidentiality, and the access of vulnerable people to mobile phones and how they use them, pose significant challenges; but they offer the opportunity to reach isolated or impoverished populations, or even to facilitate access to social and healthcare services. We close this paper formulating possible orientations, hypotheses and goals to design new investigation works involving vulnerable populations. [ABSTRACT FROM AUTHOR]

In mobile health care monitoring, compression is an essential tool for solving storage and transmission problems. The important issue is able to recover the original signal from the compressed signal. The main purpose of this paper is compressing the ECG signal with no loss of essential data and also encrypting the signal to keep it confidential from everyone, except for physicians. In this paper, mobile processors are used and there is no need for any computers to serve this purpose. After initial preprocessing such as removal of the baseline noise, Gaussian noise, peak detection and determination of heart rate, the ECG signal is compressed. In compression stage, after 3 steps of wavelet transform (db04), thresholding techniques are used. Then, Huffman coding with chaos for compression and encryption of the ECG signal are used. The compression rates of proposed algorithm is 97.72 %. Then, the ECG signals are sent to a telemedicine center to acquire specialist diagnosis by TCP/IP protocol. [ABSTRACT FROM AUTHOR]

People can use their web browser or mobile devices to access web services and applications which are built into these servers. Users have to input their identity and password to login the server. The identity and password may be appropriated by hackers when the network environment is not safe. The multiple secure authentication protocol can improve the security of the network environment. Mobile devices can be used to pass the authentication messages through Wi-Fi or 3G networks to serve as a second communication channel. The content of the message number is not considered in a multiple secure authentication protocol. The more excessive transmission of messages would be easier to collect and decode by hackers. In this paper, we propose two schemes which allow the server to validate the user and reduce the number of messages using the XOR operation. Our schemes can improve the security of the authentication protocol. The experimental results show that our proposed authentication protocols are more secure and effective. In regard to applications of second authentication communication channels for a smart access control system, identity identification and E-wallet, our proposed authentication protocols can ensure the safety of person and property, and achieve more effective security management mechanisms. [ABSTRACT FROM AUTHOR]

Decision support systems (DSS) are increasingly demanded due that diagnosis is one of the main activities that physicians accomplish every day. This fact seems critical when primary care physicians deal with uncommon problems belonging to specialized areas. The main objective of this paper is the development and user evaluation of a mobile DSS for iOS named OphthalDSS. This app has as purpose helping in anterior segment ocular diseases' diagnosis, besides offering educative content about ophthalmic diseases to users. For the deployment of this work, firstly it has been used the Apple IDE, Xcode, to develop the OphthalDSS mobile application using Objective-C as programming language. The core of the decision support system implemented by OphthalDSS is a decision tree developed by expert ophthalmologists. In order to evaluate the Quality of Experience (QoE) of primary care physicians after having tried the OphthalDSS app, a written inquiry based on the Likert scale was used. A total of 50 physicians answered to it, after trying the app during 1 month in their medical consultation. OphthalDSS is capable of helping to make diagnoses of diseases related to the anterior segment of the eye. Other features of OphthalDSS are a guide of each disease and an educational section. A 70% of the physicians answered in the survey that OphthalDSS performs in the way that they expected, and a 95% assures their trust in the reliability of the clinical information. Moreover, a 75% of them think that the decision system has a proper performance. Most of the primary care physicians agree with that OphthalDSS does the function that they expected, it is a user-friendly and the contents and structure are adequate. We can conclude that OphthalDSS is a practical tool but physicians require extra content that makes it a really useful one. [ABSTRACT FROM AUTHOR]

In this paper, two mHealth applications are introduced, which can be employed as the terminals of bigdata based health service to collect information for electronic medical records (EMRs). The first one is a hybrid system for improving the user experience in the hyperbaric oxygen chamber by 3D stereoscopic virtual reality glasses and immersive perception. Several HMDs have been tested and compared. The second application is a voice interactive serious game as a likely solution for providing assistive rehabilitation tool for therapists. The recorder of the voice of patients could be analysed to evaluate the long-time rehabilitation results and further to predict the rehabilitation process. [ABSTRACT FROM AUTHOR]

Energy profiling and estimation have been popular areas of research in multicore mobile architectures. While short sequences of system calls have been recognized by machine learning as pattern descriptions for anomalous detection, power consumption of running processes with respect to system-call patterns are not well studied. In this paper, we propose a fuzzy neural network (FNN) for training and analyzing process execution behaviour with respect to series of system calls, parameters and their power consumptions. On the basis of the patterns of a series of system calls, we develop a power estimation daemon (PED) to analyze and predict the energy consumption of the running process. In the initial stage, PED categorizes sequences of system calls as functional groups and predicts their energy consumptions by FNN. In the operational stage, PED is applied to identify the predefined sequences of system calls invoked by running processes and estimates their energy consumption. [ABSTRACT FROM AUTHOR]

The Autistic Spectrum Disorder is a cognitive disorder that affects the cognitive and motor skills; due that, users cannot perform digital and fine motor tasks. It is necessary to create software applications that adapt to the abilities of these users. In recent years has been an increase in the research of the use of technology to support autistic users to develop their communication skills and to improve learning. However, the applications' usability for disable users is not assessed objectively as the existing models do not consider interaction operators for disable users. This article focuses on identifying the operations that can easily be performed by autistic users following the metrics of KML-GOMS, TLM and FLM. In addition, users of typical development were included in order to do a comparison between both types of users. The experiment was carried out using four applications designed for autistic users. Participants were subjects divided in two groups: level 1 and level 2 autistic users, and a group of users of typical development. During the experimentation, users performed a use case for each application; the time needed to perform each task was measured. Results show that the easiest operations for autistic users are K (Keystroke), D (Drag), Initial Act (I) and Tapping (T). [ABSTRACT FROM AUTHOR]

Interdisciplinary relationships between Geography and Psychotherapy are an opportunity for innovation. Indeed, scientific works found on bibliographic databases and concerning this theme are scarce. Geographical sub-fields, such as the Geography of Emotions or Psychoanalytical Geography have started to emerge, theorizing about and interpreting feelings, emotions, moods, sufferings, of the chronically ill or diversified social groups and sites. But a less theoretical and more practical approach, in the sense of proposing, predicting and intervening, is lacking; as well as research into the possibilities offered by communication technologies and mobile phones. In the present work, we present the results of a review of the most relevant scientific works published internationally; we reflect on the contributions of Geography and mobile phones to psychosocial therapies and define the orientation and questions that should be posed in future research, from the point of view of geography and regarding psychotherapy. We conclude that the production of georeferenced data via mobile phones concerning the daily lives of people opens great possibilities for cognitive behavioural therapy and mental health. They allow for the development of personalized mood maps that locate the places where a person experiences greater or lesser stress on a daily basis; they allow for a cartography of emotions, a cognitive cartography of the places we access physically or through the Internet, of our feelings and psychosocial experiences. They open the door to the possibility of offering personalized psychotherapy treatments focusing on the ecological-environmental analysis of the places frequented by the person on a daily basis. [ABSTRACT FROM AUTHOR]

Advancements in information, communication, and sensor technologies have led to new opportunities in medical care and education. Patients in general prefer visiting the nearest clinic, attempt to avoid waiting for treatment, and have unequal preferences for different clinics and doctors. Therefore, to enable patients to compare multiple clinics, this study proposes a ubiquitous multicriteria clinic recommendation system. In this system, patients can send requests through their cell phones to the system server to obtain a clinic recommendation. Once the patient sends this information to the system, the system server first estimates the patient's speed according to the detection results of a global positioning system. It then applies a fuzzy integer nonlinear programming-ordered weighted average approach to assess four criteria and finally recommends a clinic with maximal utility to the patient. The proposed methodology was tested in a field experiment, and the experimental results showed that it is advantageous over two existing methods in elevating the utilities of recommendations. In addition, such an advantage was shown to be statistically significant. [ABSTRACT FROM AUTHOR]

This research analyzes the impact of mobile phone screen size on user comprehension of health information and application structure. Applying experimental approach, we asked randomly selected users to read content and conduct tasks on a commonly used diabetes mobile application using three different mobile phone screen sizes. We timed and tracked a number of parameters, including correctness, effectiveness of completing tasks, content ease of reading, clarity of information organization, and comprehension. The impact of screen size on user comprehension/retention, clarity of information organization, and reading time were mixed. It is assumed on first glance that mobile screen size would affect all qualities of information reading and comprehension, including clarity of displayed information organization, reading time and user comprehension/retention of displayed information, but actually the screen size, in this experimental research, did not have significant impact on user comprehension/retention of the content or on understanding the application structure. However, it did have significant impact on clarity of information organization and reading time. Participants with larger screen size took shorter time reading the content with a significant difference in the ease of reading. While there was no significant difference in the comprehension of information or the application structures, there were a higher task completion rate and a lower number of errors with the bigger screen size. Screen size does not directly affect user comprehension of health information. However, it does affect clarity of information organization, reading time and user's ability to recall information. [ABSTRACT FROM AUTHOR]

Screening for chronical diseases like type 2 diabetes can be done using different methods and various risk tests. This study present a review of type 2 diabetes risk estimation mobile applications focusing on their functionality and availability of information on the underlying risk calculators. Only 9 out of 31 reviewed mobile applications, featured in three major mobile application stores, disclosed the name of risk calculator used for assessing the risk of type 2 diabetes. Even more concerning, none of the reviewed applications mentioned that they are collecting the data from users to improve the performance of their risk estimation calculators or offer users the descriptive statistics of the results from users that already used the application. For that purpose the questionnaires used for calculation of risk should be upgraded by including the information on the most recent blood sugar level measurements from users. Although mobile applications represent a great future potential for health applications, developers still do not put enough emphasis on informing the user of the underlying methods used to estimate the risk for a specific clinical condition. [ABSTRACT FROM AUTHOR]

The article looks at a study that analyzes the usability of 24 mobile personal health records (mPHRs) for Android and iOS operating systems that were selected through an analysis process construction based on the Systematic Literature Review approach. Topics covered include definition of electronic health records according to the International Organization for Standardization, method used to search for, select, and evaluate the mPHRs, and eligibility criteria and application selection.