Efficient path key establishment for wireless sensor networks

Key predistribution schemes have been proposed as means to overcome wireless sensor network constraints such as limited communication and processing power. Two sensor nodes can establish a secure link with some probability based on the information stored in their memories, though it is not always possible that two sensor nodes may set up a secure link. In this paper, we propose a new approach that elects trusted common nodes called “Proxies” which reside on an existing secure path linking two sensor nodes. These sensor nodes are used to send the generated key which will be divided into parts (nuggets) according to the number of elected proxies. Our approach has been assessed against previously developed algorithms, and the results show that our algorithm discovers proxies more quickly which are closer to both end nodes, thus producing shorter path lengths. We have also assessed the impact of our algorithm on the average time to establish a secure link when the transmitter and receiver of the sensor nodes are “ON.” The results show the superiority of our algorithm in this regard. Overall, the proposed algorithm is well suited for wireless sensor networks

Physical Layer Security: Detection of Active Eavesdropping Attacks by Support Vector Machines

This paper presents a framework for converting wireless signals into structured datasets, which can be fed into machine learning algorithms for the detection of active eavesdropping attacks at the physical layer. More specifically, a wireless communication system, which consists of K legal users, one access point (AP) and one active eavesdropper, is considered. To cope with the eavesdropper who breaks into the system during the uplink phase, we first build structured datasets based on several different features. We then apply support vector machine (SVM) classifiers and one-class SVM classifiers to those structured datasets for detecting the presence of eavesdropper. Regarding the data, we first process received signals at the AP and then define three different features (i.e., MEAN, RATIO and SUM) based on the post-processing signals. Noticeably, our three defined features are formulated such that they have relevant statistical properties. Enabling the AP to simulate the entire process of transmission, we form the so-called artificial training data (ATD) that is used for training SVM (or one-class SVM) models. While SVM is preferred in the case of having perfect channel state information (CSI) of all channels, one-class SVM is preferred in the case of having only the CSI of legal users. We also evaluate the accuracy of the trained models in relation to the choice of kernel functions, the choice of features, and the change of eavesdropper's power. Numerical results show that the accuracy is relatively sensitive to adjusting parameters. Under some settings, SVM classifiers (or even one-class SVM) can bring about the accuracy of over 90%.Comment: All versions on this site are withdrawn because of their serious mistakes. Moreover, the contributions of the co-authors were not considered carefully. Two co-authors have little contributions, which cannot constitute any main contribution. It was a mistake when the first author forgot to update the actual authors, and he hurried to upload the incomplete and flaw file

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O USO DO FACEBOOK COMO AMBIENTE VIRTUAL DE APRENDIZAGEM: UM RELATO DE EXPERIENCIA

This article is an experience report referring to the useof Facebook as a virtual learning environment in the designand application of a course of English for specific purposesfor proficiency tests for Masters and Doctorate courses. Therelevance of the topic and the increasing demand of Mastersand Doctorate students were important to choose this topic,as these students need to prove proficiency in a foreign languagein order to finish their courses.Este artigo é um relato de experiência referente ao uso do Facebook como ambiente virtual de aprendizagem na elaboração e aplicação de um curso de inglês instrumental para a prova de proficiência de mestrado e doutorado. A relevância do tema e a grande demanda de mestrandos e doutorandos foram fatores importantes para a escolha do tema, visto que esses sujeitos precisam comprovar a proficiência em língua estrangeira para concluírem suas pós-graduações.DOI: 10.36558/rsc.v12i2.770

Intensive Olfactory Training in Post-COVID Patients: A Randomized Multicenter Clinical Trial

Introduction: Olfactory dysfunction (OD) is one of the most reported symptoms of COVID -19. Previous studies have identified olfactory training (OT) as an important treatment for postinfectious OD, but little is known about its effect after SARS-CoV-2 infection and how it can be optimized. Objective: To assess whether OT can be optimized if performed intensively, with more fragrances over a shorter period in patients with persistent OD after COVID -19. Also, to determine the presence of other variables related to OD and treatment response in this population. Method: This multicenter randomized clinical trial recruited 80 patients with persistent OD with previous COVID-19 for less than three months. The patients were divided into two groups, who received treatment with 4 and 8 essences over four weeks. Subjective assessments and the University of Pennsylvania Smell Identification Test (UPSIT) were performed before and after treatment. Results: A significant improvement in olfaction was measured subjectively and on UPSIT in both groups, but without significant differences between groups. In addition, the presence of olfactory fluctuation was associated with higher UPSIT scores. Conclusion: These data suggest that intensifying the training by increasing the number of essences for 4 weeks does not show superiority over the classical method. Moreover, a fluctuating olfactory ability seems to be related to a better score in the UPSIT

Decreased expression of haemoglobin beta (HBB) gene in anaplastic thyroid cancer and recovory of its expression inhibits cell growth

Anaplastic thyroid cancer (ATC) is one of the most fulminant and foetal diseases in human malignancies. However, the genetic alterations and carcinogenic mechanisms of ATC are still unclear. Recently, we investigated the gene expression profile of 11 anaplastic thyroid cancer cell lines (ACL) and significant decreased expression of haemoglobin beta (HBB) gene in ACL. Haemoglobin beta is located at 11p15.5, where loss of heterozygosity (LOH) was reported in various kinds of cancers, including ATC, and it has been suggested that novel tumour suppressor genes might exist in this region. In order to clarify the meaning of decreased expression of HBB in ATC, the expression status of HBB was investigated with ACL, ATC, papillary thyroid cancer (PTC) and normal human tissues. Haemoglobin beta showed significant decreased expression in ACLs and ATCs; however, in PTC, HBB expressed equal to the normal thyroid gland. In addition, HBB expressed in normal human tissues ubiquitously. To validate the tumour-suppressor function of HBB, cell growth assay was performed. Forced expression of HBB in KTA2 cell, which is a kind of ACL, significantly suppressed KTA2 growth. The mechanism of downregulation of HBB in ATC is still unclear; however, our results suggested the possibility of HBB as a novel tumour-suppressor gene