The malaria system microApp: A new, mobile device-based tool for malaria diagnosis

Background: Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority. Objective: The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood samples combined with light microscopy to identify the Plasmodium falciparum species in the ring stage of development. Methods: The system uses image processing and artificial intelligence techniques as well as a known face detection algorithm to identify Plasmodium parasites. The algorithm is based on integral image and haar-like features concepts, and makes use of weak classifiers with adaptive boosting learning. The search scope of the learning algorithm is reduced in the preprocessing step by removing the background around blood cells. Results: As a proof of concept experiment, the tool was used on 555 malaria-positive and 777 malaria-negative previously-made slides. The accuracy of the system was, on average, 91%, meaning that for every 100 parasite-infected samples, 91 were identified correctly. Conclusions: Accessibility barriers of low-resource countries can be addressed with low-cost diagnostic tools. Our system, developed for mobile devices (mobile phones and tablets), addresses this by enabling access to health centers in remote communities, and importantly, not depending on extensive malaria expertise or expensive diagnostic detection equipment.Peer ReviewedPostprint (published version

A QoS monitoring system in a heterogeneous multi-domain DVB-H platform

The MobileTV, IPTV, and DVB standards (DVB-H/T) have been defined to offer mobile users interactive multimedia services with quality of service (QoS) consistency analogous to TV services. However, the market has yet to provide effective and economical solutions for the real-time delivery of such services to the corresponding transmitters over multi-domain IP networks. The monitoring system proposed in this paper enables the QoS in the IP networks involved in the delivery of real-time multimedia content to the transmitters to be ascertained. The system utilizes the QoS parameters defined in MPEG-2 Transport Streams to detect problems occurring in the heterogeneous multi-domain IP networks. The ability to detect problems having an adverse effect on QoS allows appropriate control actions to be determined to recover the QoS across the composite IP network. The design and implementation of the proposed QoS-Monitoring system (QoS-MS) is presented, followed by analysis of experimental results that demonstrate the feasibility of the system

Developing Multimedia-based Learning on Avoiding Imprecise COVID-19 Patients

Since the Covid-19 pandemic, many doctors are not only facing challenging extra works and longer time in the hospitals, but they also encountering obscured patients who would conceal their experience or even telling lies about what they feel and what they have been doing before coming to the hospitals. This paper is intended to describe a proposed design a mobile multimedia-based learning on avoiding those imprecise Covid-19 patients. This tutorial is as a campaign how to make patients and their families not to be afraid to become stigmatized by the community, and rather chose to be risking the illness. This tutorial is created using ADDIE instructional development method, and during the developing stage, it is conducted using Multimedia Development Life Cycle according to Luther. Subjects of the research are experts in education, medical, communication science and information technology in the preliminary testing. This research is still on going and the researchers would like to present the design of the system. Research findings show that this multimedia-based learning is the most feasible model to be implemented

Development of a Proactive Fault Diagnosis for Critical System

Large-scale network environments, such as the Internet, are characterized by the presence of various devices connected at various remote locations. There is a scenario of main office connected to different branch offices in another town and cities, with the presence of central administrative system at the main office. Any problem at branches is reported to the main office, due to availability of enough resources there. However, few support tools have been developed to allow the administrators at the central office to remotely control and monitor the computers at the branches. Even, in local area network environment, diagnosing the computers on the network is always a big problem for the administrator, as he/she moves from one computer to another, running the diagnostic program and collecting report for each machine tested. This is strenuous and time consuming. To help address these problems, I have employed the concept of mobile agent to design an architecture that can remotely perform various checks and tests on computers on network, and report its findings to the server administrator as central location. This architecture was implemented with Java, using Jini lookup service to establish communication between the computers. The agent tasks were implemented in C programming language. The result of this research work shows that the use of mobile agent for remote maintenance of computers on network was found to provide an improved, efficient, and dynamic diagnostic management system. All the same, it has proven to be a substantive contributor to efficient network management

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network

Application of Smartphone Technology in the Management and Treatment of Mental Illnesses

Abstract: Background: Mental illness continues to be a significant Public Health problem and the innovative use of technology to improve the treatment of mental illnesses holds great public health relevance. Over the past decade telecommunications technology has been used to increase access to and improve the quality of mental health care. There is current evidence that the use of landline and cellular telephones, computer-assisted therapy, and videoconferencing can be effective in improving treatment outcomes. Smartphones, as the newest development in communications technology, offer a new opportunity to improve mental health care through their versatile nature to perform a variety of functions. Methods: A critical literature review was performed to examine the potential of smartphones to increase access to mental health care, reduce barriers to care, and improve patient treatment outcomes. The review was performed by searching several electronic databases using a combination of keywords related to smartphones and mental health interventions using mobile devices. Literature concerning the use of cell phones, handheld computers, and smartphones to improve access to mental health care and improve treatment outcomes was identified.Results: The majority of studies identified were feasibility and pilot studies on patients with a variety of diagnosed mental illnesses using cell phones and PDAs. Authors report that most study participants, with some exceptions, were capable of using a mobile device and found them acceptable to use. Few studies extensively measured treatment outcomes and instead reported preliminary results and presented case illustrations. Studies which used smartphones successfully used them collect data on patients and deliver multimedia interventions. Discussion: The current literature offers encouraging evidence for the use of smartphones to improve mental health care but also reflects the lack of research conducted using smartphones. Studies which examine care provider use of smartphones to improve care is encouraging but has limited generalizability to mental health care. The feasibility of patient use of smartphones is also encouraging, but questions remain about feasibility in some sub-populations, particularly schizophrenia patients. Pilot testing of mobile devices and applications can greatly increase the feasibility of using smartphones in mental health care. Patients who are unfamiliar with smartphones will likely need initial training and support in their use. Conclusion: The literature identified several ways in which smartphones can increase access to care, reduce barriers, and improve treatment outcomes. Study results were encouraging but scientifically weak. Future studies are needed replicating results of studies using cell phones and PDAs on smartphones. Larger and higher quality studies are needed to examine the feasibility, efficacy, and cost-effectiveness of smartphones to deliver multiple component interventions that improve access to mental health care and improve treatment outcomes

Internet of things–based vital sign monitoring system

Wireless network technology-based internet of things (IoT) has increased significantly and exciting to study, especially vital sign monitoring (body temperature, heart rate, and blood pressure). Vital sign monitoring is crucial to carry out to strengthen medical diagnoses and the continuity of patient health. Vital sign monitoring conducted by medical personnel to diagnose the patient's health condition is still manual. Medical staff must visit patients in each room, and the equipment used is still cable-based. Vital sign examination like this is certainly not practical because it requires a long time in the process of diagnosis. The proposed vital sign monitoring system design aims to assist medical personnel in diagnosing the patient's illness. Vital sign monitoring system uses HRM-2511E sensor for heart detection, DS18b20 sensor for body temperature detection, and MPX5050DP sensor for blood pressure detection. Vital sign data processing uses a raspberry pi as a data delivery media-based internet of things (IoT). Based on the results of the vital sign data retrieval shows that the tool designed functioning correctly. The accuracy of the proposed device for body temperature is 99.51%, heart rate is 97.90%, and blood pressure is 97.69%