Mobile Cloud Networking: Virtualisation of Cellular Networks

Virtualisation of cellular networks can be seen as a way to significantly reduce the complexity of processes, required nowadays to provide reliable cellular networks. The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN) is a EU FP7 Large-scale Integrating Project (IP) funded by the European Commission that is focusing on cloud computing concepts to achieve virtualisation of cellular networks. It aims at the development of a fully cloud-based mobile communication and application platform, or more specifically, it aims to investigate, implement and evaluate the technological foundations for the mobile communication system of Long Term Evolution (LTE), based on Mobile Network plus Decentralized Computing plus Smart Storage offered as one atomic service: On-Demand, Elastic and Pay-As-You-Go. This paper provides a brief overview of the MCN project and discusses the challenges that need to be solved.

TARWIS - A Testbed Management Architecture for Wireless Sensor Network Testbeds

With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.

UMTS base station-like exposure, well-being, and cognitive performance

BACKGROUND: Radio-frequency electromagnetic fields (RF EMF) of mobile communication systems are widespread in the living environment, yet their effects on humans are uncertain despite a growing body of literature. OBJECTIVES: We investigated the influence of a Universal Mobile Telecommunications System (UMTS) base station-like signal on well-being and cognitive performance in subjects with and without self-reported sensitivity to RF EMF. METHODS: We performed a controlled exposure experiment (45 min at an electric field strength of 0, 1, or 10 V/m, incident with a polarization of 45 degrees from the left back side of the subject, weekly intervals) in a randomized, double-blind crossover design. A total of 117 healthy subjects (33 self-reported sensitive, 84 nonsensitive subjects) participated in the study. We assessed well-being, perceived field strength, and cognitive performance with questionnaires and cognitive tasks and conducted statistical analyses using linear mixed models. Organ-specific and brain tissue-specific dosimetry including uncertainty and variation analysis was performed. RESULTS: In both groups, well-being and perceived field strength were not associated with actual exposure levels. We observed no consistent condition-induced changes in cognitive performance except for two marginal effects. At 10 V/m we observed a slight effect on speed in one of six tasks in the sensitive subjects and an effect on accuracy in another task in nonsensitive subjects. Both effects disappeared after multiple end point adjustment. CONCLUSIONS: In contrast to a recent Dutch study, we could not confirm a short-term effect of UMTS base station-like exposure on well-being. The reported effects on brain functioning were marginal and may have occurred by chance. Peak spatial absorption in brain tissue was considerably smaller than during use of a mobile phone. No conclusions can be drawn regarding short-term effects of cell phone exposure or the effects of long-term base station-like exposure on human health.

Mobile competence network for community health workers in rural Myanmar: a supportive information system that facilitates the improvement of health services.

The goal of this project is the development of international cooperation for fostering solutions to provide better access to basic healthcare services.

New Freedom through Medical Devices Based on the Global System for Mobile Communications: A Prospective Survey of 620 Users of the Swiss Limmex Emergency Wristwatch-An Original Study from Switzerland

About 500,000 elderly people in Switzerland suffer a fall each year. Thus medical attention and help are essential for these people, who mostly live alone without a caregiver. Only 3% of people aged over 65 in Switzerland use an emergency system. Personal telehealth devices allow patients to receive enough information about the appropriate treatment, as well as followup with their doctors and reports of any emergency, in the absence of any caregiver. This increases their quality of life in a cost-effective fashion. "Limmex"-a new medical emergency watch-was launched in Switzerland in 2011 and has been a great commercial success. In this paper, we give a brief review of this watch technology, along with the results of a survey of 620 users conducted by the Department of Emergency Medicine in Bern.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

PS-GANS: A Patient-Specific, Gravity Assisted Navigation System for Acetabular Cup Placement

In this paper we propose a new system that allows reliable acetabular cup placement when the THA is operated in lateral approach. Conceptually it combines the accuracy of computer-generated patient-specific morphology information with an easy-to-use mechanical guide, which effectively uses natural gravity as the angular reference. The former is achieved by using a statistical shape model-based 2D-3D reconstruction technique that can generate a scaled, patient-specific 3D shape model of the pelvis from a single conventional anteroposterior (AP) pelvic X-ray radiograph. The reconstructed 3D shape model facilitates a reliable and accurate co-registration of the mechanical guide with the patient’s anatomy in the operating theater. We validated the accuracy of our system by conducting experiments on placing seven cups to four pelvises with different morphologies. Taking the measurements from an image-free navigation system as the ground truth, our system showed an average accuracy of 2.1 ±0.7 o for inclination and an average accuracy of 1.2 ±1.4 o for anteversion.

Indigenous fodder trees can increase grazing accessibility for landless and mobile pastoralists in northern Pakistan

Degraded hillsides in Northern Pakistan are rehabilitated through social forestry campaigns using fast growing exotic trees. These plantations on former scrublands curtail access by livestock owned by landless pastoralists and create social tension. This study proposes an alternative strategy of planting indigenous fodder trees and shrubs that are well-suited to the local socio-ecological characteristics and can benefit all social segments. The choice of fodder tree species, their nutritional value and distribution within the complex socio-ecological system is explained. This study also explores the suitability of these trees at different elevations, sites and transhumant routes. Providing mobile herders with adequate fodder trees could relax social tensions and complement food security.

Evaluating the Impact of the Number of Access Points in Mobile Robots Localization Using Artificial Neural Networks

Localization is information of fundamental importance to carry out various tasks in the mobile robotic area. The exact degree of precision required in the localization depends on the nature of the task. The GPS provides global position estimation but is restricted to outdoor environments and has an inherent imprecision of a few meters. In indoor spaces, other sensors like lasers and cameras are commonly used for position estimation, but these require landmarks (or maps) in the environment and a fair amount of computation to process complex algorithms. These sensors also have a limited field of vision. Currently, Wireless Networks (WN) are widely available in indoor environments and can allow efficient global localization that requires relatively low computing resources. However, the inherent instability in the wireless signal prevents it from being used for very accurate position estimation. The growth in the number of Access Points (AP) increases the overlap signals areas and this could be a useful means of improving the precision of the localization. In this paper we evaluate the impact of the number of Access Points in mobile nodes localization using Artificial Neural Networks (ANN). We use three to eight APs as a source signal and show how the ANNs learn and generalize the data. Added to this, we evaluate the robustness of the ANNs and evaluate a heuristic to try to decrease the error in the localization. In order to validate our approach several ANNs topologies have been evaluated in experimental tests that were conducted with a mobile node in an indoor space.

A simple presurgical necrotizing enterocolitis-mortality scoring system

OBJECTIVE: To assess the relationship between early laboratory parameters, disease severity, type of management (surgical or conservative) and outcome in necrotizing enterocolitis (NEC). STUDY DESIGN: Retrospective collection and analysis of data from infants treated in a single tertiary care center (1980 to 2002). Data were collected on disease severity (Bell stage), birth weight (BW), gestational age (GA) and pre-intervention laboratory parameters (leukocyte and platelet counts, hemoglobin, lactate, C-reactive protein). RESULTS: Data from 128 infants were sufficient for analysis. Factors significantly associated with survival were Bell stage (P<0.05), lactate (P<0.05), BW and GA (P<0.01, P<0.001, respectively). From receiver operating characteristics curves, the highest predictive value resulted from a score with 0 to 8 points combining BW, Bell stage, lactate and platelet count (P<0.001). At a cutoff level of 4.5 sensitivity and specificity for predicting survival were 0.71 and 0.72, respectively. CONCLUSION: Some single parameters were associated with poor outcome in NEC. Optimal risk stratification was achieved by combining several parameters in a score.

Impact of a self-developed planning and self-constructed navigation system on skull base surgery: 10 years experience

CONCLUSION: Our self-developed planning and navigation system has proven its capacity for accurate surgery on the anterior and lateral skull base. With the incorporation of augmented reality, image-guided surgery will evolve into 'information-guided surgery'. OBJECTIVE: Microscopic or endoscopic skull base surgery is technically demanding and its outcome has a great impact on a patient's quality of life. The goal of the project was aimed at developing and evaluating enabling navigation surgery tools for simulation, planning, training, education, and performance. This clinically applied technological research was complemented by a series of patients (n=406) who were treated by anterior and lateral skull base procedures between 1997 and 2006. MATERIALS AND METHODS: Optical tracking technology was used for positional sensing of instruments. A newly designed dynamic reference base with specific registration techniques using fine needle pointer or ultrasound enables the surgeon to work with a target error of < 1 mm. An automatic registration assessment method, which provides the user with a color-coded fused representation of CT and MR images, indicates to the surgeon the location and extent of registration (in)accuracy. Integration of a small tracker camera mounted directly on the microscope permits an advantageous ergonomic way of working in the operating room. Additionally, guidance information (augmented reality) from multimodal datasets (CT, MRI, angiography) can be overlaid directly onto the surgical microscope view. The virtual simulator as a training tool in endonasal and otological skull base surgery provides an understanding of the anatomy as well as preoperative practice using real patient data. RESULTS: Using our navigation system, no major complications occurred in spite of the fact that the series included difficult skull base procedures. An improved quality in the surgical outcome was identified compared with our control group without navigation and compared with the literature. The surgical time consumption was reduced and more minimally invasive approaches were possible. According to the participants' questionnaires, the educational effect of the virtual simulator in our residency program received a high ranking.

Augmented reality endoscopic system (ARES): preliminary results

During endoscopic surgery, it is difficult to ascertain the anatomical landmarks once the anatomy is fiddled with or if the operating area is filled with blood. An augmented reality system will enhance the endoscopic view and further enable surgeons to view hidden critical structures or the results of preoperative planning.

An integrated system for 3D hip joint reconstruction from 2D X-rays: a preliminary validation study

The acquisition of conventional X-ray radiographs remains the standard imaging procedure for the diagnosis of hip-related problems. However, recent studies demonstrated the benefit of using three-dimensional (3D) surface models in the clinical routine. 3D surface models of the hip joint are useful for assessing the dynamic range of motion in order to identify possible pathologies such as femoroacetabular impingement. In this paper, we present an integrated system which consists of X-ray radiograph calibration and subsequent 2D/3D hip joint reconstruction for diagnosis and planning of hip-related problems. A mobile phantom with two different sizes of fiducials was developed for X-ray radiograph calibration, which can be robustly detected within the images. On the basis of the calibrated X-ray images, a 3D reconstruction method of the acetabulum was developed and applied together with existing techniques to reconstruct a 3D surface model of the hip joint. X-ray radiographs of dry cadaveric hip bones and one cadaveric specimen with soft tissue were used to prove the robustness of the developed fiducial detection algorithm. Computed tomography scans of the cadaveric bones were used to validate the accuracy of the integrated system. The fiducial detection sensitivity was in the same range for both sizes of fiducials. While the detection sensitivity was 97.96% for the large fiducials, it was 97.62% for the small fiducials. The acetabulum and the proximal femur were reconstructed with a mean surface distance error of 1.06 and 1.01 mm, respectively. The results for fiducial detection sensitivity and 3D surface reconstruction demonstrated the capability of the integrated system for 3D hip joint reconstruction from 2D calibrated X-ray radiographs.

SLA-driven predictive orchestration for distributed cloud-based mobile services

We describe a system for performing SLA-driven management and orchestration of distributed infrastructures composed of services supporting mobile computing use cases. In particular, we focus on a Follow-Me Cloud scenario in which we consider mobile users accessing cloud-enable services. We combine a SLA-driven approach to infrastructure optimization, with forecast-based performance degradation preventive actions and pattern detection for supporting mobile cloud infrastructure management. We present our system's information model and architecture including the algorithmic support and the proposed scenarios for system evaluation.