Secure Information Flow for IoT Applications

This paper discusses how to ensure security, i.e., confidentiality and integrity properties, for data in IoT applications. While confidentiality could be assessed via information flow analysis, integrity is ensured by error-correcting codes. In addition to errors, many communication channels also cause erasures, i.e., the demodulator cannot decide which symbol the received waveform represents. The paper proposes a method that might correct both errors and erasures together. Our method is efficient in reducing memory storage as well as decoding complexity

Évaluation des risques environnementaux liés au tourisme littoral : l’exemple de Can Gio (municipalite de Hô Chi Minh-Ville)

Le district de Can Gio est situé dans la zone littorale de la municipalité de Hô Chi Minh-Ville. Grâce aux avantages de sa situation géographique et à son statut de réserve de biosphère mondiale de mangrove, cette localité est devenue une des destinations touristiques principales de la ville. Toutefois, face aux changements apportés à l’environnement par les catastrophes naturelles ainsi que par les activités anthropiques, il est nécessaire de comparer les avantages et les inconvénients d’une exploitation du potentiel touristique. Pour ce faire, nous avons utilisé les standards de gestion des risques AS/NZS 4360 : 2004 et la méthode du quotient pour examiner les risques environnementaux qui pourraient nuire au développement touristique. Les premiers résultats montrent que typhons, tornades, nappes de pétrole et pollution de l’eau sont des risques qui demandent une attention particulière lors de l’établissement de stratégies de gestion des risques, ainsi que lors de la mise en œuvre d’une planification de l’aménagement du territoire et du développement du tourisme local.Can Gio is the only littoral district of Ho Chi Minh City. Possessing a long seashore and the mangrove biosphere reserve, Can Gio is now one of most attractive tourist destinations in Ho Chi Minh City. However, the impacts of natural hazards and human activities on this area raise the question of assessing risks for tourism. From the standpoint that touristic resources would be touched in the first place by environmental turbidity, we concentrate our evaluating effort on coastal sea resources. Based on the guidelines of Risk Management AS/NZS 4360: 2004 and the Quotient method, some environmental risks for coastal tourism have been assessed. The preliminary results show that typhoons, tornadoes, oil spills and pollution due to organic and industrial wastes reach a high level of risk and need particular attention when setting risk management strategies and tourism development plan for Can Gio

Évaluation des risques environnementaux liés au tourisme littoral : l’exemple de Can Gio (municipalite de Hô Chi Minh-Ville)

Le district de Can Gio est situé dans la zone littorale de la municipalité de Hô Chi Minh-Ville. Grâce aux avantages de sa situation géographique et à son statut de réserve de biosphère mondiale de mangrove, cette localité est devenue une des destinations touristiques principales de la ville. Toutefois, face aux changements apportés à l’environnement par les catastrophes naturelles ainsi que par les activités anthropiques, il est nécessaire de comparer les avantages et les inconvénients d’une exploitation du potentiel touristique. Pour ce faire, nous avons utilisé les standards de gestion des risques AS/NZS 4360 : 2004 et la méthode du quotient pour examiner les risques environnementaux qui pourraient nuire au développement touristique. Les premiers résultats montrent que typhons, tornades, nappes de pétrole et pollution de l’eau sont des risques qui demandent une attention particulière lors de l’établissement de stratégies de gestion des risques, ainsi que lors de la mise en œuvre d’une planification de l’aménagement du territoire et du développement du tourisme local.Can Gio is the only littoral district of Ho Chi Minh City. Possessing a long seashore and the mangrove biosphere reserve, Can Gio is now one of most attractive tourist destinations in Ho Chi Minh City. However, the impacts of natural hazards and human activities on this area raise the question of assessing risks for tourism. From the standpoint that touristic resources would be touched in the first place by environmental turbidity, we concentrate our evaluating effort on coastal sea resources. Based on the guidelines of Risk Management AS/NZS 4360: 2004 and the Quotient method, some environmental risks for coastal tourism have been assessed. The preliminary results show that typhoons, tornadoes, oil spills and pollution due to organic and industrial wastes reach a high level of risk and need particular attention when setting risk management strategies and tourism development plan for Can Gio

Improved bowel function in patients with spina bifida after bone marrow-derived mononuclear cell transplantation: A report of 2 cases

Objective: Congenital defects/diseases Background: Bowel dysfunction is observed in 42.2–71.2% of patients with spina bifida. Traditional treatments yield limited results. The objective of this paper is to report on improvement in bowel function in 2 children with spina bifida following bone marrow-derived mononuclear cells transplantation. Case reports: Two patients – 14 years old and 11 years old – with bowel dysfunction after myelomeningocele repair underwent 2 BMMNC transplantations without complications. Those patients had normal defecation, assessed through follow-ups of 21 months and 16 months, respectively. Conclusions: BMMNC transplantation can improve bowel function, as demonstrated in 2 patients with spina bifida

A Proposed CNN Model for Audio Recognition on Embedded Device

The audio detection system enables autonomous cars to recognize their surroundings based on the noise produced by moving vehicles. This paper proposes the utilization of a machine learning model based on convolutional neural networks (CNN) integrated into an embedded system supported by a microphone. The system includes a specialized microphone and a main processor. The microphone enables the transmission of an accurate analog signal to the main processor, which then analyzes the recorded signal and provides a prediction in return. While designing an adequate hardware system is a crucial task that directly impacts the predictive capability of the system, it is equally imperative to train a CNN model with high accuracy. To achieve this goal, a dataset containing over 3000 up-to-5-second WAV files for four classes was obtained from open-source research. The dataset is then divided into training, validation, and testing sets. The training data is converted into images using the spectrogram technique before training the CNN. Finally, the generated model is tested on the testing segment, resulting in a model accuracy of 77.54%

Energy-Efficient Design for Downlink Cloud Radio Access Networks

This work aims to maximize the energy efficiency of a downlink cloud radio access network (C-RAN), where data is transferred from a baseband unit in the core network to several remote radio heads via a set of edge routers over capacity-limited fronthaul links. The remote radio heads then send the received signals to their users via radio access links. We formulate a new mixed-integer nonlinear problem in which the ratio of network throughput and total power consumption is maximized. This challenging problem formulation includes practical constraints on routing, predefined minimum data rates, fronthaul capacity and maximum RRH transmit power. By employing the successive convex quadratic programming framework, an iterative algorithm is proposed with guaranteed convergence to a Fritz John solution of the formulated problem. Significantly, each iteration of the proposed algorithm solves only one simple convex program. Numerical examples with practical parameters confirm that the proposed joint optimization design markedly improves the C-RAN's energy efficiency compared to benchmark schemes.This work is supported in part by an ECR-HDR scholarship from The University of Newcastle, in part by the Australian Research Council Discovery Project grants DP170100939 and DP160101537, in part by Vietnam National Foundation for Science and Technology Development under grant number 101.02-2016.11 and in part by a startup fund from San Diego State University

User Selection Approaches to Mitigate the Straggler Effect for Federated Learning on Cell-Free Massive MIMO Networks

This work proposes UE selection approaches to mitigate the straggler effect for federated learning (FL) on cell-free massive multiple-input multiple-output networks. To show how these approaches work, we consider a general FL framework with UE sampling, and aim to minimize the FL training time in this framework. Here, training updates are (S1) broadcast to all the selected UEs from a central server, (S2) computed at the UEs sampled from the selected UE set, and (S3) sent back to the central server. The first approach mitigates the straggler effect in both Steps (S1) and (S3), while the second approach only Step (S3). Two optimization problems are then formulated to jointly optimize UE selection, transmit power and data rate. These mixed-integer mixed-timescale stochastic nonconvex problems capture the complex interactions among the training time, the straggler effect, and UE selection. By employing the online successive convex approximation approach, we develop a novel algorithm to solve the formulated problems with proven convergence to the neighbourhood of their stationary points. Numerical results confirm that our UE selection designs significantly reduce the training time over baseline approaches, especially in the networks that experience serious straggler effects due to the moderately low density of access points.Comment: submitted for peer review

Spectral and Energy Efficiency Maximization for Content-Centric C-RANs with Edge Caching

This paper aims to maximize the spectral and energy efficiencies of a content-centric cloud radio access network (C-RAN), where users requesting the same contents are grouped together. Data are transferred from a central baseband unit to multiple remote radio heads (RRHs) equipped with local caches. The RRHs then send the received data to each group's user. Both multicast and unicast schemes are considered for data transmission. We formulate mixed-integer nonlinear problems in which user association, RRH activation, data rate allocation, and signal precoding are jointly designed. These challenging problems are subject to minimum data rate requirements, limited fronthaul capacity, and maximum RRH transmit power. Employing successive convex quadratic programming, we propose iterative algorithms with guaranteed convergence to Fritz John solutions. Numerical results confirm that the proposed joint designs markedly improve the spectral and energy efficiencies of the considered content-centric C-RAN compared to benchmark schemes. Importantly, they show that unicasting outperforms multicasting in terms of spectral efficiency in both cache and cache-less scenarios. In terms of energy efficiency, multicasting is the best choice for the system without cache whereas unicasting is best for the system with cache. Finally, edge caching is shown to improve both spectral and energy efficiencies.This work is supported in part by an ECRHDR scholarship from The University of Newcastle, in part by the Australian Research Council Discovery Project grants DP170100939 and DP160101537