Jiangxi University of Finance and Economics

About: Jiangxi University of Finance and Economics is a education organization based out in Nanchang, China. It is known for research contribution in the topics: Fuzzy logic & China. The organization has 2865 authors who have published 3556 publications receiving 41567 citations.

Driving forces for low carbon technology innovation in the building industry: A critical review

Abstract: As a response to climate change, low carbon development has attracted a growing public attention. It is urgent to implement low carbon economy through technological innovation so that carbon emissions can be reduced effectively. The synergy and cooperation amongst the participants is required due to various challenges such as: multi-participants, multi-objectives and multi-technologies. These present significant challenges to the low carbon technology (LCT) innovation development. The objective of this study is to identify the relevant driving forces of LCT innovation and their interaction in the construction industry. This paper firstly analyzes the interrelationships of the participants via a methodology of system dynamics (SD) and questionnaire survey. The main driving forces and related influential factors are highlighted by means of a deductive method. Moreover, a SD model is established to examine the driving forces where government and private firms all play a role. The results show that LCT integration driving forces are significantly influenced by the continuous changes of a particular low carbon project as well as the number of participating enterprises. All the driving forces reflect an increasingly level of effectiveness. According to the model simulation, it will take a long period of time to transform traditional projects to low carbon projects. China needs at least 21 years that the quantity of low carbon buildings exceeds that of traditional ones. As a result, the building and construction industry is facing a significant challenge in terms of carbon emissions reduction. The numbers of enterprises participating in LCT innovation will not always increase with the enhancement of driving forces. Rather, it will keep at a stable level after a certain growth. A particular one single driving force has limited impact on the growth of low carbon projects and participating enterprises. System integration plays a crucial role to achieve the low carbon development.

An efficient biometrics-based authentication scheme for telecare medicine information systems

Abstract: The telecare medical information system enables the patients gain health monitoring and access healthcare-related services over internet or mobile networks. Due to the open environment, the mutual authentication between the user and the telecare server will thus be in demand. Many smart card based authentication schemes for telecare medicine information systems have been proposed for the goals. However, most of the schemes are vulnerable to various attacks. Specially, some schemes require the exponential computation or public key cryptography which leads to very low efficiency for smart card. This paper proposes an efficient smart card based password authentication scheme by applying biometrics technique and hash function operations. It is shown to be more secure and practical for telecare medicine environments. Streszczenie. W artykule opisano prostą metode uwierzytelniania i identyfikacji uzytkownika danych uslug (np. medycznych) na podstawie kart typu Smart-Card. Proponowana struktura opiera sie na technikach biometrycznych oraz funkcji skrotu (haszowanie). Rozwiązanie to zapewnia wieksze bezpieczenstwo i jest praktyczniejsze dla telefonicznych biur obslugi medycznej. (Zastosowanie techniki biometrii w strukturze uwierzytelniania klienta dla telefonicznych biur obslugi ośrodkow medycznych).

Structured Joint Sparse Principal Component Analysis for Fault Detection and Isolation

Abstract: In order to improve the performance of fault isolation and diagnosis of principal component analysis (PCA) based methods, this article proposes a novel fault detection and isolation approach using the structured joint sparse PCA (SJSPCA). The objective function involves two regularization terms: the $l_{2,1}$ norm and the graph Laplacian. By imposing the $l_{2,1}$ norm, SJSPCA is able to achieve row-wise sparsity, and introducing the graph Laplacian term can incorporate structured variable correlation information. The row-sparsity property of $l_{2,1}$ norm ensures that the score indices associated with normal variables approaching zero and the graph Laplacian constraint helps the isolation of correlated faulty variables. Once a fault is detected, a two-stage fault-isolation strategy is considered and a score index is calculated for each variable. It is proved that the proposed two-stage strategy is capable of isolating faulty variables. The improved fault-isolation performance of SJSPCA is illustrated by a simulation example and a gas flow fault observed in an industrial blast furnace iron-making process.