Decentralized federated learning methods for reducing communication cost and energy consumption in UAV networks

Unmanned aerial vehicles (UAV) or drones play many roles in a modern smart city such as the delivery of goods, mapping real-time road traffic and monitoring pollution. The ability of drones to perform these functions often requires the support of machine learning technology. However, traditional machine learning models for drones encounter data privacy problems, communication costs and energy limitations. Federated Learning, an emerging distributed machine learning approach, is an excellent solution to address these issues. Federated learning (FL) allows drones to train local models without transmitting raw data. However, existing FL requires a central server to aggregate the trained model parameters of the UAV. A failure of the central server can significantly impact the overall training. In this paper, we propose two aggregation methods: Commutative FL and Alternate FL, based on the existing architecture of decentralised Federated Learning for UAV Networks (DFL-UN) by adding a unique aggregation method of decentralised FL. Those two methods can effectively control energy consumption and communication cost by controlling the number of local training epochs, local communication, and global communication. The simulation results of the proposed training methods are also presented to verify the feasibility and efficiency of the architecture compared with two benchmark methods (e.g. standard machine learning training and standard single aggregation server training). The simulation results show that the proposed methods outperform the benchmark methods in terms of operational stability, energy consumption and communication cost.Comment: 13 pages, 7 figure

Dissimilitudes entre les contenus géométriques du manuel scolaire mathématiques de 8e année en Iran et le test international du TIMSS 2011

Les résultats de la cinquième réalisation de l'étude de TIMSS en 2011 montrent la présence d'un faible rendement des élèves iraniens en mathématiques par rapport à la moyenne internationale. Plusieurs facteurs peuvent être à la source de ce faible rendement : programmes d'études, caractéristiques de l'école, qualité des ressources éducatives fournies à l'école ou accessibles aux élèves hors de l'école, etc. (Mullis et coll., 2009; 2012; Coleman et coll., 1966). Ce mémoire est une tentative d'identifier les points faibles probables du contenu géométrique du manuel scolaire de mathématiques de 8e année de l'Iran, en considérant les exigences de TIMSS 2011. Dans cette perspective, cette recherche se focalise sur trois axes d'analyse : la répartition des contenus géométriques dans le manuel des mathématiques, la manière de présenter les concepts et les niveaux de raisonnement exigés par les problèmes du test et par les activités du manuel. L'analyse des résultats obtenus nous a permis de constater plusieurs divergences. Au niveau de la présence des connaissances géométriques, 9 % des connaissances nécessaires à la résolution des questions de TIMSS 2011 sont absentes du manuel. Quant à la présentation des connaissances, 27 % des connaissances sont présentées implicitement dans les manuels. L'utilisation de la grille d'analyse du niveau de raisonnement exigé par les tâches géométriques (Tanguay, 2000), montre que le manuel manque d'exercices mettant en jeu le développement des expériences mentales (35 %). Selon la théorie de Van Hiele (1959), l'insuffisance d'expériences nécessaires pour le développement de la pensée géométrique aux niveaux visuel, descriptif et analytique influencera la construction des concepts et la réussite dans la résolution des problèmes

The prevention of endothelial dysfunction through endothelial cell apoptosis inhibition in a hypercholesterolemic rabbit model: the effect of L-arginine supplementation

<p>Abstract</p> <p>Background</p> <p>The impact of L-arginine on atherogenesis and its ability to prevent endothelial dysfunction have been studied extensively during the past years. L-arginine is a substance for nitric oxide synthesis which involves in apoptosis. Hypercholesterolemia promotes endothelial dysfunction, and it is hypothesized that L-arginine prevents endothelial dysfunction through endothelial cells apoptosis inhibition. To test this hypothesis, thirty rabbits were assigned into two groups. The control group received 1% cholesterol diet for 4 weeks, and the L-arginine group received same diets plus 3% L-arginine in drinking water.</p> <p>Results</p> <p>No significant differences were observed in cholesterol level between two groups, but the nitrite concentration in L-arginine group was significantly higher than other group (control group: 11.8 ± 1; L-arginine group: 14.7 ± 0.5 μmol/l); (<it>p </it>< 0.05). The aorta score of fatty streak in control group was 0.875 ± 0.35, but no fatty streak lesion was detected in L-arginine group (<it>p </it>< 0.05). The number of intimal apoptotic cells/500 cells of aorta in two groups of experiment were statistically different (control group: 39.3 ± 7.6; L-arginine group: 21.5 ± 5.3) (<it>p </it>< 0.05).</p> <p>Conclusion</p> <p>The inhibition of endothelial cells apoptosis by L-arginine restores endothelial function in a model of hypercholesterolemia.</p

Corporate Capital Structure Decisions: Evidence from an Emerging Market

Abstract: This study investigates the determinants of capital structure of listed firms in the Tehran Stock Exchange using both static and dynamic approaches over the period 2003 to 2011. This study employs two alternative leverage measures (including book leverage and market leverage) as dependent variables and seven factors (including profitability, growth opportunity, liquidity, business risk, effective tax rate, size and tangibility) as determinants of capital structure. We provide evidence that although capital structure theories could be portable to Iran but, there are several major differences indicating that specific features of Iranian capital market are at work

The Relationship between Psychological Status (Depression and Anxiety) and Social Support and Sexual Function

AbstractIntroduction: Given that large numbers of marital problems arise from lack of proper satisfaction with sexual desire (libido) as well as lack of awareness towards the complicated dimensions of this fundamental motive, the purpose of the present study was to determine correlations between psychological state (depression and anxiety), social support, and sexual function among females of the reproductive age.Methods: This study was a descriptive-analytic research on 400 females referred to clinics affiliated with Shahid Beheshti University of Medical Sciences in the city of Tehran, during year 2015. The study sample was recruited by cluster and multi-stage random sampling method. The Sexual Function Questionnaire, Demographic Questionnaire, Scale of Perceived Social Support, Spielberger’s Anxiety Inventory, and Beck Depression Inventory were also used to collect the data. The obtained data was analyzed through the SPSS software via descriptive statistics, t test, one way Analysis of Variance (ANOVA), as well as chi-square test.Results: The findings revealed that 4.5% of females had poor level of sexual functioning. In addition, 24.5% of females benefited from low social support and also 75% and 9% of the given individuals had chronic depression and severe anxiety, respectively. According to the results of this study, sexual functioning was correlated with female’s age, husband’s age, age of first pregnancy, length of marriage, duration of having private rooms, and history of infertility (P ˂ 0.05). Furthermore, there were relationships between sexual functioning and depression as well as anxiety and social support (P ˂ 0.05).Conclusions: It was concluded that sexual functioning was correlated with psychological state (depression and anxiety) and social support. Thus, it was recommended to conduct screening tests in terms of the variables examined

Distinct neurocomputational mechanisms support informational and socially normative conformity

A change of mind in response to social influence could be driven by informational conformity to increase accuracy, or by normative conformity to comply with social norms such as reciprocity. Disentangling the behavioural, cognitive, and neurobiological underpinnings of informational and normative conformity have proven elusive. Here, participants underwent fMRI while performing a perceptual task that involved both advice-taking and advice-giving to human and computer partners. The concurrent inclusion of 2 different social roles and 2 different social partners revealed distinct behavioural and neural markers for informational and normative conformity. Dorsal anterior cingulate cortex (dACC) BOLD response tracked informational conformity towards both human and computer but tracked normative conformity only when interacting with humans. A network of brain areas (dorsomedial prefrontal cortex (dmPFC) and temporoparietal junction (TPJ)) that tracked normative conformity increased their functional coupling with the dACC when interacting with humans. These findings enable differentiating the neural mechanisms by which different types of conformity shape social changes of mind