JAEC

Honorary Editor-in-Chief
Le Vinh Danh
, Ton Duc Thang University, Vietnam
ISSN: ...
Chairmain of the Editorial Board
Václav SnášelTechnical University of Ostrava, Czech Republic

 

 

AIMS & SCOPE
Journal of Advanced Engineering and Computation (JAEC) is a forum for the presentation of innovative ideas, approaches, developments, and research projects in the area of advanced engineering and computation. It serves to facilitate the exchange of information between researchers and industry professionals. Multi-disciplinary topics that connect the core areas of advanced engineering and computation and its applications are also covered in this journal.

It also aims to promote and coordinate developments in the field of advanced engineering and computation. The international dimension is emphasized in order to foster international collaboration in advanced engineering and computation to meet the needs of broadening the applicability and scope of the current body of knowledge.

READERSHIP
The journal provides a vehicle to help professionals, academics, researchers and policy makers working in fields relevant to advanced engineering and computation to disseminate information and to learn from each other's work.

CONTENTS
JAEC publishes original papers, review papers, technical reports, case studies, conference reports, management reports, book reviews, notes, commentaries and news. 

Research Open Access
Lukas Macula , Miroslav Voznak
2017
Today, network technologies can handle throughputs up to 100Gbps, transporting 200 million packets per second on a single link. Such high bandwidths impact network flow analysis and as a result require significantly more powerful hardware. Methods used today concentrate mainly on analyzes of data flows and patterns. It is nearly impossible to actively look for anomalies in network packets and flows for a small amount of change of monitoring patterns could result in big increases in potentially false positive incidents. This paper focuses on multi-criteria analyzes of systems generated data in order to predict incidents. We prove that systems generated monitoring data are an appropriate source to analyze and enable for much more focused and less computationally intensive monitoring operations. By using appropriate mathematical methods to analyze stored data it is possible to obtain useful information. During our work, some interesting anomalies in networks were found by utilizing simple data correlations using monitoring system Zabbix. We concluded that it is possible to declare that deeper analysis is possible due to Zabbix monitoring system and its features like Open-Source core, documented API and SQL backend for data. The result of this work is a new approach to the analysis containing algorithms which allow to identify significant items in monitoring system.
Research Open Access
Jaroslav Pokorny
2017
Comparing graph databases with traditional,e.g., relational databases, some important database features are often missing there. Particularly, a graph database schema including integrity constraints is mostly not explicitly defined, also a conceptual modelling is not used. It is hard to check a consistency of the graph database, because almost no integrity constraints are defined or only their very simple representatives can be specified. In the paper, we discuss these issues and present current possibilities and challenges in graph database modelling. We focus also on integrity constraints modelling and propose functional dependencies between entity types, which reminds modelling functional dependencies known from relational databases. We show a number of examples of often cited GDBMSs and their approach to database schemas and ICs specification. Also a conceptual level of a graph database design is considered. We propose a sufficient conceptual model based on a binary variant of the ER model and show its relationship to a graph database model, i.e. a mapping conceptual schemas to database schemas. An alternative based on the conceptual functions called attributes is presented.
Research Open Access
Tuan Le Anh
2017
This paper presents an extended Kalman filtering (EKF) algorithm for estimating immeasurable state variables of a vehicle stability control system. Initially, the steering angle and vertical forces on the tires were considered inputs of the estimator. The measured process outputs were the sensor signals egarding longitudinal and lateral accelerations, steering angle, yaw rate, and wheel speed. Subsequently, by using Euler discretization for a seven-degree-of-freedom nonlinear vehicle model, difficult-to-measure state variables such as lateral velocity, vehicle side-slip angle, and lateral tire forces were identified separately by using the EKF algorithm. The estimation results of the proposed control system evidenced high performance.
Research Open Access
Dung Quang Nguyen
2017
Fractional-order controllers are recognized to guarantee better closed-loop performance and robustness than conventional integer-order controllers. However, fractional-order transfer functions make time, frequency domain analysis and simulation signi cantly di cult. In practice, the popular way to overcome these di culties is linearization of the fractional-order system. Here, a systematic approach is proposed for linearizing the transfer function of fractional-order systems. This approach is based on the real interpolation method (RIM) to approximate fractional-order transfer function (FOTF) by rational-order transfer function. The proposed method is implemented and compared to CFE high-frequency method; Carlson’s method; Matsuda’s method; Chare ’s method; Oustaloup’s method; least-squares, frequency interpolation method (FIM). The results of comparison show that, the method is simple, computationally e cient, exible, and more accurate in time domain than the above considered methods.
Research Open Access
Lenka Skanderova
2017
In this paper, the dynamics of the selected variants of the di erential evolution is modelled by aggregated network capturing the relationships between individuals established during the population evolution. The motivation of this research is to better understand the relationships between individuals of the selected variants of the di erential evolution. Thanks to the analysis of the aggregated networks, the advantages as well as bottlenecks of the selected algorithms can be speci ed more precisely and the results of the analysis can be used to develop novel algorithms.
Research Open Access
Phuong Minh Tran , Thanh Nhan Nguyen
2017
We study the long time behavior of the bounded solutions of non homogeneous gradient-like system which admits a strict Lyapunov function. More precisely, we show that any bounded solution of the gradient-like system converges to an accumulation point as time goes to in nity under some mild hypotheses. As in homogeneous case, the key assumptions for this system are also the angle condition and the Kurdyka-Lojasiewicz inequality. The convergence result will be proved under a L1 -condition of the perturbation term. Moreover, if the Lyapunov function satis es a Lojasiewicz inequality then the rate of convergence will be even obtained.
To be updated...