Key Management Techniques for Wireless Mesh Network

Key management is one of the most important tasks in wireless mesh network. This service is responsible for key generation, distribution, and key exchange in a cryptography-based system. Due to the shared nature of WMNs and absence of globally trusted central authority, key management becomes more challenging. This chapter introduces several key management methods that can address these challenges. The fundamental approach is the secret sharing scheme created by A. Shamir, which effectively distributes keys to all participants’ network. Based on Shamir’s scheme, many authors proposed other algorithms to secure the communication channel in such a way that adversary cannot steal any information about the secret. In addition, in this chapter, a new secret sharing method using real-time synchronization among transceiver devices is presented. In this method, each node generates its key depending on its physical information and the real-time clock. Therefore, public and private keys can be managed efficiently for data encryption and prevent several external attacks to WMNs. A specific protocol is proposed to secure keys while transferring between devices to prevent internal attacks

The DKAP Project The Country Report of Vietnam

Viet Nam is at the beginning of the Fourth Industrial Revolution. In order to grasp the opportunities that the revolution has brought about, and to successfully build the society of digital citizens, there must be the demand of enhancing the capacity and capability for students to meet international standards in terms of Information and Communications Technology (ICT) skills. Viet Nam was selected as one of the four countries (Viet Nam, Bangladesh, Fiji, and the Republic of Korea) to join UNESCO Bangkok’s “Digital Kids Asia Pacific (DKAP)” project, a comparative cross-national study with the aim to seek the understanding and address children’s ICT practices, attitudes, behaviors, and competency levels within an educational context. Thanks to the project, the Vietnamese research team completely conducted the survey in twenty (20) schools from five (5) provinces in Viet Nam. With the data on the digital citizenship competency levels of 1,061 10th grade students, the research team discovered the valuable findings to draw an initial big picture for Vietnamese policy makers, educators, and teachers about digital citizenship competencies of 15-year-old Vietnamese students

Improved mitochondrial amino acid substitution models for metazoan evolutionary studies

Abstract Background Amino acid substitution models play an essential role in inferring phylogenies from mitochondrial protein data. However, only few empirical models have been estimated from restricted mitochondrial protein data of a hundred species. The existing models are unlikely to represent appropriately the amino acid substitutions from hundred thousands metazoan mitochondrial protein sequences. Results We selected 125,935 mitochondrial protein sequences from 34,448 species in the metazoan kingdom to estimate new amino acid substitution models targeting metazoa, vertebrates and invertebrate groups. The new models help to find significantly better likelihood phylogenies in comparison with the existing models. We noted remarkable distances from phylogenies with the existing models to the maximum likelihood phylogenies that indicate a considerable number of incorrect bipartitions in phylogenies with the existing models. Finally, we used the new models and mitochondrial protein data to certify that Testudines, Aves, and Crocodylia form one separated clade within amniotes. Conclusions We introduced new mitochondrial amino acid substitution models for metazoan mitochondrial proteins. The new models outperform the existing models in inferring phylogenies from metazoan mitochondrial protein data. We strongly recommend researchers to use the new models in analysing metazoan mitochondrial protein data

CURRENT SITUATION OF STUDENTS’ PSYCHOLOGICAL STATE BEFORE PRACTICAL COURSES’ FINAL EXAMS

The article aimed to determine the factors influencing students’ psychological state before the final exam of practical courses. The article used conventional scientific research methods in sports and physical training combined with psychological tests studied on fifty students at Ho Chi Minh City University of Physical Education and Sports (UPES). After reviewing related studies and consulting with experts, four tests were employed to assess the psychological state before the test of the research subjects. The results showed that students with a good psychological state to take the exam had good test results. Conversely, students with a feverish or lethargic state will have poor test results. The research results serve as the basis for proposing measures to adjust the psychological state before the exam, contributing to improving the learning results of students.  Article visualizations

FLU, an amino acid substitution model for influenza proteins

Abstract Background The amino acid substitution model is the core component of many protein analysis systems such as sequence similarity search, sequence alignment, and phylogenetic inference. Although several general amino acid substitution models have been estimated from large and diverse protein databases, they remain inappropriate for analyzing specific species, e.g., viruses. Emerging epidemics of influenza viruses raise the need for comprehensive studies of these dangerous viruses. We propose an influenza-specific amino acid substitution model to enhance the understanding of the evolution of influenza viruses. Results A maximum likelihood approach was applied to estimate an amino acid substitution model (FLU) from ~113, 000 influenza protein sequences, consisting of ~20 million residues. FLU outperforms 14 widely used models in constructing maximum likelihood phylogenetic trees for the majority of influenza protein alignments. On average, FLU gains ~42 log likelihood points with an alignment of 300 sites. Moreover, topologies of trees constructed using FLU and other models are frequently different. FLU does indeed have an impact on likelihood improvement as well as tree topologies. It was implemented in PhyML and can be downloaded from ftp://ftp.sanger.ac.uk/pub/1000genomes/lsq/FLU or included in PhyML 3.0 server at http://www.atgc-montpellier.fr/phyml/. Conclusions FLU should be useful for any influenza protein analysis system which requires an accurate description of amino acid substitutions.</p

Modelling and Experimental Validation of a VNT Turbocharger for Improving Performances of a Marine Diesel Generator Engine

This paper presents modelling and experimental validation for improving the performances of a marine diesel generator engine. Based on the diesel engine theory, the laws of conservation of energy, and the principle of movement of flow through turbocharger nozzle, a mathematical model of a real turbocharged engine was built, concentrating on the mathematic model of flow through nozzles. This model is simulated by Matlab/Simulink program, the results of simulation showed the relationships between the engine and the turbocharger, the turbine and the compressor, and between the nozzles and the turbocharger. The experiments were carried out to validate this model, the errors between the simulation and measure were acceptable. The measure and simulation results also determined that at the low load conditions (≤50% load) engine performances can be improved by adjusting nozzle opening degree (from fully opening to 90% and 80% opening)

A Robust Mobile Robot Navigation System using Neuro-Fuzzy Kalman Filtering and Optimal Fusion of Behavior-based Fuzzy Controllers

This study proposes a control system model for mobile robots navigating in unknown environments. The proposed model includes a neuro-fuzzy Extended Kalman Filter for localization task and a behaviorbased fuzzy multi-controller navigation module. The neuro-fuzzy EKF, used for estimating the robot’s position from sensor readings, is an enhanced EKF whose noise covariance matrix is progressively adjusted by a fuzzy neural network. The navigation module features a series of independently-executed fuzzy controllers, each deals with a specific navigation sub-task, or behavior, and a multi-objective optimizer to coordinate all behaviors. The membership functions of all fuzzy controllers play the roles of objective functions for the optimizer, which produces an overall Pareto-optimal control signal to drive the robot. A number of simulations and real-world experiments were conducted to evaluate the performance of this model

Real-time Key Management for Wireless Mesh Network

With the rapid technological development of wireless, wireless mesh network (WMN) is one of the network models which is gradually showing its superiority through several applications and projects thus it is becoming the key of technology for IoT. Due to the vulnerable environment, limited resource and open communication channel, the security design for such networks are significantly challenging. By using realtime synchronization method between transceiver devices in the WMNs, we propose an algorithm based on secret sharing method in which each node generate its key depend on its physical information and the real-time clock. Therefore, we can manage efficiently public and private keys for data encryption and prevent several external attacks to WMNs. We also propose a specific protocol to secure our keys while transferring between devices to prevent internal attacks