On the Interference Alignment Designs for Secure Multiuser MIMO Systems

In this paper, we propose two secure multiuser multiple-input multiple-output transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. When the channel state information is perfectly known at all Txs, in each proposed IA scheme, the precoding matrices at Txs and the receive subspaces at Rxs or the eavesdropper are alternatively selected to minimize the cost function of an convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of average secrecy sum rate.Comment: Updated version, updated author list, accepted to be appear in IEICE Transaction

HYBRID END-TO-END APPROACH INTEGRATING ONLINE LEARNING WITH FACE-IDENTIFICATION SYSTEM

To date, facial recognition has been one of the most intriguing, interesting research topics over years. It requires some specific face-based algorithms such as facial detection, facial alignment, facial representation, and facial recognition as well; however, all of these algorithms derive from heavy deep learning architectures that cause limitations for development, scalability, flawed accuracy, and deployment into publicity with mere CPU servers. It also calls for large datasets containing hundreds of thousands of records for training purposes. In this paper, we propose a full pipeline for an effective face recognition application which only uses a small Vietnamese celebrity dataset and CPU for training that can solve the leakage of data and the need for GPU devices. It is based on a face vector-to-string tokens algorithm then saves face’s properties into Elasticsearch for future retrieval, so the problem of online learning in Facial Recognition is also tackled. Comparison with another popular algorithm on the dataset, our proposed pipeline not only outweighs the accuracy counterpart, but it also achieves a very speedy time inference for a real-time face recognition application

Seawater desalination using air gap membrane distillation-an experimental study on membrane scaling and cleaning

The connection between operating temperature and membrane scaling/cleaning during an air gap membrane distillation (AGMD) process of seawater has been systematically elucidated in this study. Experimental and mathematically simulated data demonstrate the profound influences of feed salinity and membrane scaling on water flux at various operating temperatures. Feed salinity exerted significant impacts on water flux at high operating temperatures because of aggravated polarization effects. Membrane scaling and the subsequent membrane cleaning efficiency were also strongly affected by operating temperatures. Indeed, membrane scaling was more severe and occurred at a lower water recovery when operating at 60-50 °C (feed-coolant temperature) compared to that at 35-25 °C. Moreover, membrane cleaning with fresh water and vinegar was less effective for the membrane scaled at 60-50 °C compared to 35-25 °C. Finally, membrane cleaning using vinegar was much more efficient than fresh water. Given the availability of vinegar at household level, vinegar cleaning can potentially be a low cost and readily accessible approach for MD maintenance for small scale seawater desalination applications in remote coastal communities

Numerical and Experimental Study on the Grinding Performance of Ti-Based Super-Alloy

The experiments of the surface grinding of Ti-6Al-4V grade 5 alloy (Ti-64) with a resin-bonded cubic Boron Nitride (cBN) grinding wheel are performed in this research to estimate the influence of cutting parameters named workpiece infeed speed, Depth of Cut (DOC), cooling condition on the grinding force, force ratio, and specific energy. A finite element simulation model of single-grain grinding of Ti-64 is also implemented in order to predict the values of grinding forces and temperature. The experimental results show that an increase of workpiece infeed speed creates higher intensified cutting forces than the DOC. The grinding experiments under wet conditions present slightly lower tangential forces, force ratio, and specific energy than those in dry grinding. The simulation outcomes exhibit that the relative deviation of simulated and experimental forces is in the range of 1-15%. The increase in feed rate considerably reduces grinding temperature, while enhancement of DOC elevates the heat generation in the cutting zone

Réduction de modèles issus de la méthode PEEC pour la modélisation électromagnétique des interconnexions électriques

Le sujet de cette thèse traite de l'amélioration de la méthode PEEC inductive (permettant une modélisation des interconnexions électriques d'un point de vue électromagnétique basse fréquence) en employant une méthode de compression matricielle FMM. L'introduction de ces compressions entraîne des restrictions concernant les opérations algébriques autorisées, seule les opérations de type produit matrice - vecteur sont permises. L'objectif était de proposer des méthodes pour déterminer : Les courants en tout point du dispositif Des impédances équivalentes entre différents ports d'entrées-sorties. Le premier point a pu être traité en mettant en place une méthode originale de recherche d'un jeu d'équations indépendantes ainsi qu'un préconditionneur spécifique dans la phase de résolution compatible avec les méthodes de compression matricielle. Le second point a nécessité l'utilisation de méthode de réduction d'ordre à base de sous espace de Krylov afin de construire un développement limité des jeux d'impédance recherché. Ensuite, nous avons mis en place une technique de synthèse de circuit afin d'obtenir un circuit électrique simple permettant de modéliser le comportement du dispositif avec de simples éléments de type résistance, inductance (non couplée) et capacité. Cette démarche permet l'utilisation dans tous les simulateurs temporels et ainsi permet d'avoir une vision système légère du dispositif d'interconnexion électrique.This thesis deals with the improvement of the inductive PEEC method (for modelling electrical interconnections of low frequency) using the matrix compression Fast Multipole Method (FMM). The introduction of FMM leads to only algebraic operation of type matrix - vector product is permitted. The objective of this thesis was to propose some methods to determine: Currents at any point of the device The equivalent impedances between different input-output ports. The first point has been treated by introducing a novel method to determine a set of independent equations. The choice of iterative methods in solving linear system imposed on the establishment of a specific preconditioner compatible with matrix compression methods. The second point require to describe the Kirchoff law in the form of state space equation and to use model order reduction method based on Krylov subspace to compute Taylor series of impedance matrix. Once again, all the steps are necessary to be taked into account the use of matrix compression method FMM. Following our order reduction method, we implemented a circuit synthesis technique to obtain a simple electrical circuit which conserve the behavior of the device by simple elements like resistance, inductance (uncoupled) and capacity. This approach allows the reuse of reduction model in all time domain simulation software. For global system, it provides also a light model of electrical interconnection device.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Embedding Sustainable Consumption into Higher Education in Vietnam

Changing in the way that human produces and consumes are indispensable to achieve sustainable consumption. All of the countries in developed economies, economies in transition and developing economies should promote sustainable consumption. This will require larger changes in society. Higher education plays a vital role in promoting understanding, awareness of professors, staff members and students of sustainable consumption. Through higher education, these people would be positively change their mind about this issue. National Economics University (NEU) is one of the leading university in economics in Vietnam as a case study. Students graduated from the university will be future experts, leaders and businessmen. After graduation, as academic citizens with acquainted knowledge and skills, they will influence the economic and social changes though their business and private purchasing habits and decisions. Using data from the University, this paper will reveal the current landscape of sustainable consumption at National Economics University through the years. In order to embed this issues into education, the university should incorporate sustainable consumption into the curriculum, create and implement a sustainability plan and adjust teaching method to encourage students asking questions, analyzing, thinking critically and making decisions toward sustainable consumption. Keywords: Embedding sustainable consumption, higher education DOI: 10.7176/EJBM/11-18-12 Publication date:June 30th 201

Choosing the best machine tool in mechanical manufacturing

Machine tools are indispensable components and play an important role in mechanical manufacturing. The equipment of machine tools has a huge effect on the operational efficiency of businesses. Each machine tool type is described by many different criteria, such as cost, technological capabilities, accuracy, energy consumption, convenience in operation, safety for workers, working noise, etc. If the selection of machine is only based on one or several criteria, it will be really easy to make mistakes, which means it is not possible to choose the real best machine. A machine is considered to be the best only when it is chosen based on all of its criteria. This work is called multi-criteria decision-making (MCDM). In this study, the selection of machine tools has been done using two different multi-criteria decision-making methods, including the FUCA method (Faire Un Choix Adéquat) and the CURLI method (Collaborative Unbiased Rank List Intergration). These are two methods with very different characteristics. When using the FUCA method, it is necessary to normalize the data and determine the weights for the criteria. Meanwhile, if using the CURLI method, these two things are not necessary. The selection of these two distinct methods is intended to produce the most generalizable conclusions. Three types of machine tool, which are considered in this study, include grinding machine, drilling machine and milling machine. The number of grinders that were offered for selection was twelve, the number of drills that were surveyed in this study was thirteen, while nine were the number of milling machines that were given for selection. The objective of this study is to determine the best solution in each type of machine. The results of ranking the machines are very similar when using the two mentioned methods. Specially, in all the surveyed cases, the two methods FUCA and CURLI always find the same best alternative. Accordingly, it is possible to firmly come to a conclusion that the FUCA method and the CURLI method are equally effective in machine tool selection. In addition, this study has determined the best three machines corresponding to the three different machine type

HYDROGEN-PLASMA-TREATED NANO TIO2 FOR PHOTOCATALYTIC OXIDATION OF VOCS IN AIR STREAM

Unlike water treatment processes, the photocatalytic oxidation of VOCs in air stream exhibits many challenges. This study will develop the hydrogen-plasma-treated TiO2 with improvement in photocatalytic activity. The hydrogen-plasma-treatment was carried out in the non-thermal atmospheric pressure reactor at room temperature or above. The catalysts were prepared and analyzed by advanced techniques such as X-ray diffraction (XRD), scanning electro-microscopy (SEM) and transmission electro-microscopy (TEM). The photocatalytic activity of the catalyst has been investigated under UV light with various reaction conditions such as different initial toluene/formaldehyde concentrations and water content. Significantly, the conversion of toluene by a plasma-treated sample was 1.5 times higher than the bare TiO2 in a similar reaction condition